CN103562940A - Manage an organization's computing resources under a computing environment entitlement contract - Google Patents

Abstract

Mechanisms are provided for reserving computing resources of a data processing system. These mechanisms generate one or more Computing Environment Entitlement Contract (CEEC) data structures, each of which defines the terms of a service level agreement between a contracting party and a provider of the data processing system. These mechanisms associate a collection of computing resources with the CEEC data structures. The mechanisms then manage the collection of one or more computing resources according to the associated CEECs. Such management includes invalidating or revoking the CEEC data structures in response to the contracting party failing to utilize computing resources from a selected group of computing resources for a specified purpose, at a specified level and intensity pattern, approximately during a specified time period, as identified in the CEEC data structures.

Description

Manage an organization's computing resources under a computing environment entitlement contract

technical field

The present application relates generally to an improved data processing apparatus and method and more particularly to managing computing resources of an organization in accordance with an established computing environment entitlement contract.

Background technique

Investment in computing resources represents a significant expense for large organizations in today's society. Large organizations such as the U.S. federal government, individual departments and agencies of government, and corporations such as IBM in Armonk, New York, Bank of America, General Electric, Citigroup, and many others, can have thousands of various Computers of various types, configurations, capabilities, and levels of efficiency. Managing all of these computing resources so that these organizations use them efficiently and optimally is a daunting task. Efficient and optimal use of these computing resources includes identifying unutilized, underutilized, or simply obsolete technologies for decommissioning and replacement.

A major obstacle to optimizing an organization's computing resources is the reluctance of organizational personnel to change. That is, when people are issued computing resources (e.g., laptops, desktops, etc.), they treat the computing resources as if they were fully dedicated to them, i.e., employees have full access to those computing resources regardless of whether they actually use them. 100% rights to. This gives the employee a sense of confidence that if at any time the employee needs computing resources, they will be available because the employee has 100% entitlement to those computing resources. As a result, employees are reluctant to give up those computing resources for other computing resources to which employees feel they are given less than 100% entitlement to the computing resources, such as in a shared computing resource environment (e.g., virtualized computing environment, etc.). That is, even though the computing resources may not be utilized, or at least not fully utilized by the employees, the employees will not give up those computing resources, because no matter how inefficient or obsolete the computing resources may be, they will still rather remain confident that these computing resources will be available to them rather than Not to run the risk that new computing resources might not be available when they need them.

Additionally, mechanisms are known to allocate computing resources to employees, but there is no mechanism for determining whether those computing resources are being used by the employee for the business purpose for which the employee was given those computing resources. Thus, it is often possible to assign a computing resource to an employee, and the employee may use the computing resource, but not to achieve the computing resource's intended business purpose and may in fact use the computing resource for another purpose. Thus, although it may appear that computing resources are being utilized, they are in fact not being used to benefit the organization. There are no known mechanisms for detecting such situations and then addressing them to optimize the benefit to the organization's allocation of computing resources.

Mechanisms are needed for incentivizing employees to ditch unutilized, underutilized, or obsolete computing resources for new computing resources in a manner that gives them a sense of confidence that their needs will be met with the new computing resources. Additionally, mechanisms are needed for detecting situations as a whole where computing resources are not being used to achieve the business purpose for which they are allocated and then addressing these situations in order to optimize the allocation of computing resources for the benefit of the organization.

Furthermore, there is currently weak support for defining "use" of computing resources other than performing atomic workloads. "Using" a computing resource, as its users imagine it to be, is typically time-scaled in months rather than seconds, encompassing any number of different interleaved workloads, and including expected periods of non-use, which can last for multiple days . Thus, much more than simply discovering the execution environment for atomic workloads involves optimizing the environment in which "use" is thus defined.

Contents of the invention

In one illustrative embodiment, a method for reserving computing resources of a data processing system in a data processing system including at least one computing device and a plurality of computing resources. The method includes establishing, by at least one computing device, one or more Computing Environment Entitlement Contract (CEEC) data structures, each CEEC data structure defining terms of a business level agreement between a contractor and a provider of the data processing system. The terms of the CEEC specify a collection of computing resources with a specified configuration to be used by the contractor for a specified purpose at a specified level and intensity pattern for a specified period of time.

The method also includes associating, by at least one computing device, the set of one or more computing resources with the CEEC data structure. Additionally, the method includes managing, by the at least one computing device, the set of one or more computing resources according to the associated CEEC data structure. In response to the contractor's failure to utilize the computing resources of the selected group of computing resources for the specified purpose approximately at the specified level and intensity pattern during the specified time period, the logic of the data processing system then invalidates the CEEC data structure.

In other exemplary embodiments, a computer program product comprising a computer-usable or readable medium having a computer-readable program is provided. The computer readable program, when executed on the computing device, causes the computing device to perform various operations and combinations of the operations outlined above with respect to the exemplary embodiments of the method.

In yet another exemplary embodiment, a system/apparatus is provided. The system/apparatus may include one or more processors and one or more memories coupled to the one or more processors. The one or more memories may include instructions that, when executed by the one or more processors, cause the one or more processors to perform various operations and combinations of the operations outlined above with respect to the exemplary embodiments of the method.

These and other features and advantages of the invention will be described in or will become apparent to those of ordinary skill in the art in view of the following detailed description of the example embodiments of the invention.

Description of drawings

The invention, together with its preferred mode of use, together with further objects and advantages, will be best understood by reference to the following detailed description of illustrative embodiments when read in conjunction with the accompanying drawings, in which:

1 is an example diagram of a distributed data processing system in which aspects of the illustrative embodiments may be implemented;

FIG. 2 is an example diagram of a computing device in which aspects of the illustrative embodiments may be implemented;

FIG. 3 is an illustration of a primary operating computing device for implementing a computing environment rights contract based management system, according to an illustrative embodiment;

Figure 4 is an example diagram of a Computing Environment Entitlement Contract (CEEC) data structure, according to an example embodiment;

FIG. 5 is a flowchart outlining example operations for generating associations of groups, according to an illustrative embodiment;

FIG. 6 is an example diagram of a group profile data structure according to an exemplary embodiment;

7 is a flowchart outlining example operations for generating a computing resource utilization score, according to an illustrative embodiment;

8 is a flowchart outlining example operations for selecting exemplary and counter-exemplary members of a group and using this selection to define evaluation criteria and associated actions in a profile, according to an illustrative embodiment;

FIG. 9 is a flowchart outlining example operations for assessing CEEC compliance, according to an illustrative embodiment;

10A-10D are example diagrams illustrating various stages of a transaction for an example CEEC market maker-based scenario, according to an example embodiment;

11A-11C depict example diagrams of transaction specifications according to an illustrative embodiment; and

FIG. 12 is a flowchart outlining example operations for executing a CEEC market transaction, according to an illustrative embodiment.

Detailed ways

The illustrative embodiments provide a mechanism for managing an organization's computing resources in accordance with an established Computing Environment Entitlement Contract (CEEC). Utilizing the mechanisms of the exemplary embodiments, a CEEC is established for each pairing of a contractor with one or more computing resources of an organization, typically having hundreds to thousands of computing resources of various types, configurations, capabilities, uses, etc. Large-scale organization of computing resources. Using CEEC as a tool for pairing a counterparty with an appropriate computing resource, evaluating a counterparty's utilization of a computing resource associated with a counterparty, dynamically reassigning a counterparty to an appropriate computing resource, matching CEEC in a market maker environment The basis for buyers and sellers of computing resources and for performing other computing resource management operations as described below. As a result of managing computing resources based on these CEECs, workloads can be balanced, migrated, managed, etc. to optimize utilization of the organization's computing resources. However, this workload management, balancing, migration, etc. is based on the results of these CEECs managing computing resources and not the primary mechanism for achieving efficiency. That is, the object of optimization is the totality of the managed computing environment, the execution of any given workload of that computing environment is a fraction that itself does not inherently and naturally define CEEC.

CEEC is an explicit agreement that a given party (e.g., an individual, group, department, division, company, etc.) will A given set of one or more computing resources (eg, hardware and/or software resources) configured in a manner (thus defining a computing environment) for a given business purpose. A given level may be expressed, for example, as a minimum, maximum, average or other representation of the quantity utilized. Utilization intensity patterns may be defined at a plurality of given utilization levels at one or more specified intervals over a given time period. CEECs may also define migration criteria that limit migration capabilities for migrating CEECs from one set of computing resources to another set of computing resources. Each CEEC may be defined in one or more data structures accessible by one or more hardware and/or software mechanisms of the illustrative embodiments to implement the computing resource management operations set forth below.

A data processing system according to an exemplary embodiment includes logic for enforcing CEEC on both the data processing system and an identified contractor such that whether or not the identified contractor will be specified in the CEEC The collection of computing resources is actually used for the specified business purpose. The collection of computing resources or a part of the collection of computing resources is reserved for use by the identified contractor, and if the contractor fails to transfer the computing resources to Aggregation for a specified business purpose invalidates the CEEC. That is, CEEC is enforceable on the computing resource provider side regardless of whether the contracting party actually utilizes the computing resource under CEEC. At the same time, however, if the contractor fails to utilize a computing resource subject to the CEEC in accordance with the terms of the CEEC, the data processing system may annul or deny the CEEC so that it is not enforceable on either the computing resource provider or the contractor. implement. Typically, such a repudiation is linked to the replacement of the CEEC with a new CEEC that is more appropriate for the contracting party's use of computing resources, where the new CEEC may be related to a previous CEEC that may differ from one or more computing resources associated with the now repudiated CEEC. A new collection association of one or more computing resources of the collection. Authority to deny CEEC is provided by an enterprise/organization that ultimately owns computing resources and benefits from their use and that has employed the mechanisms of one or more of the exemplary embodiments of the present invention.

CEEC also provides a mechanism through which valuation and buying and selling of rights to computing resources can be performed in the market maker mechanism. This market maker mechanism establishes a market for exchanging CEECs and thus their associated workloads and capacities, however, this is not a "free market". It is a marketplace that is owned by a particular organization and managed so as to serve the specific interests of the particular organization. That is, rather than simply determining the highest bidder as in a free market system, the CEEC market maker of an exemplary embodiment may allow specific organizations to define preferences for matching buyers and sellers of CEECs within the established market. Thus, a given business/organization leverages market power to ensure that its value is enhanced and realized by the transactions executed via the market.

A simple example of CEEC and its use in a CEEC-based computing resource management system is a corporation, eg, International Business Machines (IBM) Corporation of Armonk, NY, which provides laptop computers to employees. In this scenario, the computing resource can be considered as a laptop computer, and the contractor can be considered as an employee, while the provider of the computing resource is a company, namely IBM Corporation. When assigning laptops to employees, the CEEC is established to govern the provider's requirements for providing laptops to employees (i.e., the employee's entitlement to computing resources) and the employee's requirements for a given utilization level and intensity pattern (e.g., utilizing laptop resources at approximately 50% utilization during business hours, Monday through Friday, 9am to 5pm for a given time period such as 1 year) will be configured in a given manner Both are requirements of a laptop computer (eg, having a specific set of hardware and/or software to achieve a specified business purpose) for a specified business purpose (eg, software development). The system can then monitor the employee's utilization of the laptop according to the CEEC and control the transfer of CEECs between buyers and sellers, denial of CEECs, creation of new CEECs for employees, etc. based on the terms specified in the CEEC.

For example, the data processing system of the illustrative embodiments may be implemented by determining how often an employee utilizes a laptop computer, what processes are Monitor the employee's use of the laptop as well as any other metrics that indicate the employee's utilization of computing resources (laptops) under the CEEC. From this monitoring, it can be determined whether the employee utilizes the laptop within a given tolerance of the terms specified in the CEEC, and if not, the difference between the employee's actual use of the laptop and the Whether the difference between expected exploits becomes the basis for exchanging CEECs, denying CEECs and creating CEECs, or other administrative actions. Swapping, denying, creating, or other administrative operations associated with CEECs may also result in computing resources associated with CEECs being swapped or otherwise reclaimed and/or reallocated by a computing resource provider (eg, IBM Corporation).

This example could be extended to consider two laptops - one for traditional business use during core business hours and the other for occasional customer demonstrations no more often than once a month, expected between demonstrations Do not use. These are two different CEECs that encapsulate very different predictions for utilization intensity patterns.

This could also be expanded to add a server expected to be used 24/7 at a moderate intensity level that hosts a customer facing website available to customers across all time zones. Also, quite different CEEC packages have very different predictions for utilization intensity patterns.

Thus, CEEC specifies not only for providers of computing resources requirements for a particular set of one or more computing resources configured in a particular way (i.e., in a particular computing Requirements for utilization as specified by the contracting parties. This differs significantly from known contractual relationships between contractors (eg, users) and providers of computing resources in several ways. For example, one known contractual relationship between a user and a provider of computing resources is known as a Service Level Agreement (SLA). With an SLA, the provider of a computing resource is required to provide a specific level of service defined in general terms (e.g., specific bandwidth, bit rate, mean time between failures, mean time to recovery, jitter, etc.) In exchange for payment by the user for that indicated level of service. There is no requirement on the part of the user to use computing resources for any specific business purpose, etc. at a specified level of utilization intensity or pattern; the only requirement on the user is that the user pay for the indicated level of service.

Similarly, another type of contractual relationship between users and providers of computing resources is called a Quality of Service (QoS) agreement, in which a certain level of performance is provided for the data flows in the system as a whole Ensure, for example, the desired bit rate, latency, jitter, packet loss probability, bit error rate, etc. Likewise, users are not required to use the system for specific business purposes, etc. at specified levels of utilization intensity or patterns. The only requirement on the user is that the user pay for the quality of service.

Traditional cloud computing mechanisms are based on such SLA or QoS type arrangements. That is to say, when a user contracts with a cloud computing resource provider, the user contracts for a general service level or service quality and does not care how to provide this service level or service quality, that is, does not care what specific computing resources are used to provide services level or quality of service. A user simply accesses the "cloud" and expects a particular level of service or quality of service to be provided in whatever manner the cloud resource provider determines to provide that level or quality of service. Likewise, there is no requirement for users to actually use the cloud's resources for any specific business purpose at any minimum level of intensity, any minimum utilization pattern, etc. All the user is required to do is pay for the SAL or QoS they want from the cloud. Another way to describe this is that the cloud is non-judgmental in its consideration of resource usage - it neither knows nor cares what business purpose, if any, the set of allocated resources is used to deliver. This contrasts with an enterprise's goals when allocating funds to the cloud -- the enterprise does so in anticipation of achieving a specific business outcome.

Thus, one of the main differences between CEEC and known contractual relationships between parties and providers of computing resources is that the parties in CEEC are required to utilize computing resources at specified levels or else CEEC can be denied, Exchange, etc. and may require the parties to relinquish the parties' rights to the associated computing resources that the parties have under the CEEC. If an existing CEEC is denied, a new CEEC may be generated or an existing CEEC may be reassociated with a new set of one or more computing resources. New associations of new CEECs or existing CEECs may be performed based on the measured utilization of computing resources by the counterparties and computing resource capabilities, configurations, etc. in order to comply most closely with the counterparty's utilization of computing resources and/or The closest compliance is made to the requirements under new or existing CEEC. As described below, this is all done within an organized market as established by a market maker system operating on a collection of CEECs and computing resources. The organization's market is defined in terms of achieving the most efficient allocation of computing resources to contractors as may be defined by criteria specified by the organization. These and other mechanisms of the exemplary embodiments are described in more detail below.

Those skilled in the art know that various aspects of the present invention can be implemented as a system, method or computer program product. Accordingly, various aspects of the invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.), or an embodiment combining hardware and software aspects, where Collectively referred to as "circuits", "modules" or "systems". Furthermore, various aspects of the present invention may also take the form of a computer program product embodied in one or more computer-readable media having computer-usable program code embodied thereon.

Any combination of one or more computer readable medium(s) may be utilized. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (non-exhaustive list) of computer readable storage media would include the following: electrical connection with one or more conductors, portable computer disk, hard disk, random access memory (RAM), read only memory (ROM ), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In the context of this document, a computer-readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device.

A computer readable signal medium may include a data signal carrying computer readable program code, for example, in baseband or as part of a carrier wave. Such a propagated signal may take many forms, including but not limited to electromagnetic, optical, or any suitable combination of the foregoing. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can communicate, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device .

Computer code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, radio frequency (RF), etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages—such as Java (Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its subsidiaries), Smalltalk ^TM , C++, etc., and conventional procedural programming languages—such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server . In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or wide area network (WAN), or it can be connected to an external computer (for example, by using an Internet service provider). provider's Internet).

Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to exemplary embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine such that when executed by the processor of the computer or other programmable data processing apparatus, the Create means for implementing the functions/actions specified in one or more blocks in flowcharts and/or block diagrams.

These computer program instructions can also be stored in a computer-readable medium, and these instructions direct a computer, other programmable data processing device, or other equipment to work in a specific manner, so that the instructions stored in the computer-readable medium produce An article of manufacture of instructions for functions/actions specified in one or more blocks in a flowchart and/or block diagram.

Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other equipment, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other equipment to produce a computer-implemented process, Thus, the instructions executed on the computer or other programmable devices provide a process for realizing the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a portion of code that includes one or more programmable logic components for implementing specified logical functions. Execute instructions. It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. It should also be noted that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or actions , or may be implemented by a combination of dedicated hardware and computer instructions.

Accordingly, the illustrative embodiments may be utilized in many different types of data processing environments, including distributed data processing environments, a single data processing device, and the like. To provide a context for describing specific elements and functions of the example embodiments, Figures 1 and 2 are provided below as example environments in which aspects of the example embodiments may be implemented. It should be understood that FIGS. 1-2 are examples only and are not intended to assert or imply any limitation as to the environments in which aspects or embodiments of the invention may be practiced. Many modifications to the depicted environments may be made without departing from the spirit and scope of the invention.

Referring now to the drawings, FIG. 1 depicts a diagrammatic representation of an example distributed data processing system in which aspects of the illustrative embodiments may be implemented. Distributed data processing system 100 may include a network of computers in which aspects of the illustrative embodiments may be implemented. Distributed data processing system 100 includes at least one network 102 , which is the medium used to provide communication links between various devices and computers connected together within distributed data processing system 100 . Network 102 may include connections, such as wires, wireless communication links, or fiber optic cables.

In the depicted example, server 104 and server 106 are connected to network 102 along with storage unit 108 . Additionally, clients 110 , 112 and 114 are also connected to network 102 . These clients 110, 112, and 114 may be, for example, personal computers, network computers, and the like. In the depicted example, server 104 provides data, such as boot files, operating system images, and applications, to clients 110, 112, and 114. Clients 110 , 112 , and 114 are clients to server 104 in the depicted example. Distributed data processing system 100 may include additional servers, clients, and other devices not shown.

In the depicted example, distributed data processing system 100 is the Internet with network 102 , which represents a worldwide collection of networks and gateways that use the Transmission Control Protocol/Internet Protocol (TCP/IP) suite of protocols to communicate with each other. At the heart of the Internet is a backbone of high-speed data communication links between major nodes, or host computers, made up of thousands of commercial, governmental, educational and other computer systems that route data and messages. Of course, distributed data processing system 100 may also be implemented to include many different types of networks, such as, for example, intranets, local area networks (LANs), wide area networks (WANs), and the like. As noted above, FIG. 1 is intended as an example and not as an architectural limitation for different embodiments of the invention, and thus the particular elements shown in FIG. 1 should not be considered as pertaining to an exemplary implementation in which the invention may be practiced. The example environment is limited.

Referring now to FIG. 2 , shown is a block diagram of an example data processing system in which aspects of the illustrative embodiments may be implemented. Data processing system 200 is an example of a computer, such as client 110 in FIG. 1 , in which computer usable code or instructions implementing the processes for the illustrative embodiments of this invention may reside.

In the depicted example, data processing system 200 employs a hub architecture that includes North Bridge and Memory Controller Hub (NB/MCH) 202 and South Bridge and Input/Output (I/O) Controller Hub (SB/ICH) 204. Processing unit 206 , main memory 208 and graphics processor 210 are connected to NB/MCH 202 . Graphics processor 210 may be connected to NB/MCH 202 through an accelerated graphics port (AGP).

In the depicted example, local area network (LAN) adapter 212 is connected to SB/ICH 204 . Audio adapter 216, keyboard and mouse adapter 220, modem 222, read only memory (ROM) 224, hard disk drive (HDD) 226, CD-ROM drive 230, universal serial bus (USB) port and other communication ports 232, and PCI/ PCIe device 234 is connected to SB/ICH 204 via bus 238 and bus 240 . PCI/PCIe devices may include, for example, Ethernet adapters, add-in cards, and PC Cards for notebook computers. PCI uses a card bus controller while PCIe does not. ROM 24 may be, for example, a fast basic input/output system (BIOS).

HDD 226 and CD/ROM drive 230 are connected to SB/ICH 204 via bus 240 . HDD 226 and CD-ROM drive 230 may use, for example, integrated drive electronics (IED) or a serial advanced technology attachment (SATA) interface. Super I/O (SIO) devices 236 may be connected to SB/ICH 204 .

An operating system runs on the processing unit 206 . The operating system coordinates and provides control of the various components within data processing system 200 in FIG. 2 . As a client, the operating system can be a commercially available operating system, such as Microsoft Windows7 (Microsoft and Windows are trademarks of Microsoft Corporation in the United States, other countries, or both). An object-oriented programming system, such as a Java programming system, can run in conjunction with an operating system and provide calls to the operating system from Java programs or applications executing on data processing system 200 (Java is a trademark of Oracle and/or its subsidiaries).

)操作系统或者LINUX操作系统的

eServer^TM 计算机系统（IBM、eServer、System p和AIX是国际商业机器公司在美国、其他国家或者二者的商标，而LINUX是Linux Torvalds在美国、其他国家或者二者的商标）。数据处理系统200可以是包括处理单元206中的多个处理器的对称多处理器（SMP）系统。备选地，可以运用单处理器系统。As a server, the data processing system 200 can be, for example, running Advanced Interactive Executive (

) operating system or LINUX operating system

eServer ^™ Computer Systems (IBM, eServer, System p, and AIX are trademarks of International Business Machines Corporation in the United States, other countries, or both, and LINUX is a trademark of Linux Torvalds in the United States, other countries, or both). Data processing system 200 may be a symmetric multiprocessor (SMP) system including multiple processors in processing unit 206 . Alternatively, a single processor system may be employed.

Instructions for the operating system, object-oriented programming system, and applications or programs reside on storage devices such as HDD 226 and may be loaded into main memory 208 for execution by processing unit 206 . Processing unit 206 may, for example, use computer usable program code which may be located in memory (eg, main memory 208 , ROM 224 ) or in one or more peripheral devices 226 and 230 to carry out the processes for the exemplary embodiments of the present invention.

A bus system, such as bus 238 or bus 240 as shown in FIG. 2, may include one or more buses. Of course, the bus system may be implemented using any type of communication structure or architecture that provides for data transfer between different components or devices attached to the structure or architecture. A communications unit such as modem 222 or network adapter 212 of FIG. 2 may include one or more devices used to transmit and receive data. The memory may be, for example, main memory 208 , ROM 224 , or a cache such as found in NB/MCH 202 in FIG. 2 .

Those of ordinary skill in the art will understand that the hardware in FIGS. 1-2 may vary depending on the implementation. Other internal hardware or peripherals, such as flash memory, equivalent non-volatile memory, or optical disc drives, etc. may be used in addition to or instead of the hardware depicted in FIGS. 1-2. The processes of the illustrative embodiments may also be applied to multiprocessor data processing systems other than the previously mentioned SMP systems without departing from the spirit and scope of the present invention.

Additionally, data processing system 200 may employ any data processing system from a number of different data processing systems, including client computing devices, server computing devices, tablet computers, laptop computers, telephones or other communication devices, personal digital assistants (PDAs), and the like. The form of the processing system. In some illustrative examples, data processing system 200 may be, for example, a portable computing device configured with flash memory to provide nonvolatile memory for storing operating system files and/or user-generated data. In essence, data processing system 200 may be any known or later developed data processing system without architectural limitation.

Many network-based systems (such as the system shown in Figure 1 or its equivalent) can be coupled together to create a network of computing resources of an organization (eg, a corporation, government, private sector, or other legal entity). These computing resources may include a small collection of computing resources of various types, capabilities, configurations, etc., such as tens to hundreds of computing resources, or may include a large collection of computing resources, such as thousands of computing resources. For example, a computing resource may range from a desktop computer, a laptop computer, a printer, a router, a switch, a storage device, a specific processor within a computing device, a memory or portion of memory, a network device or appliance, or any other computing resource. Each of these computing resources may be of a different type, capability, configuration, etc. such that, for example, an organization may have thousands of desktop computers, some of which may have x86 processor chips and others may have cell mother chips. Board engine processor chips, others may have P7 processor chips, and each may have different numbers of processor cores, different software resources loaded on the processor cores, etc., so that different types, configurations and capabilities are provided.

One or more servers or other computing devices of an organization's network of computing resources may be configured to provide hardware and/or software mechanisms for implementing a CEEC-based computing resource management system according to the exemplary embodiments described herein. For example, one or more servers and/or network-attached storage devices may be provided for establishing, storing, and managing CEECs and associating these CEECs with particular contractors and one or more particular groups of computing resources. In some example embodiments, the mechanisms of the example embodiments may interface with existing organizational systems (such as human resources systems, etc.) to associate CEECs with specific contractors and specific computing resources.

In addition, one or more servers and/or network-attached storage systems may be provided as configuration management database (CMDB) systems for obtaining and storing configuration information about computing resources of an organization's network of computing resources. Additionally, one or more servers or other computing devices of the organization's network of computing resources may be configured to provide market maker services, group management services, leverage scoring services, deal builder services as will be described in more detail below , group and profile management services, system utilization management services, etc.

General Situation of Resource Management System Based on CEEC

3 is an illustration of a primary operating computing device for implementing a computing environment rights contract based management system, according to an illustrative embodiment. The units shown in FIG. 3 may be implemented, for example, as software instructions executed by one or more processors of one or more computing devices (eg, servers, etc.). In some demonstrative embodiments, some of the mechanisms shown in FIG. 3 may be implemented entirely within the hardware of a computing system, for example, as a dedicated hardware device (e.g., an application-specific integrated circuit (ASIC)) or the like or as a combination of hardware and software. A combination of, for example, firmware, etc. The scope of the example embodiments is intended to cover, without limitation, all hardware embodiments as well as embodiments comprising a combination of hardware and software, in any particular configuration determined to be suitable for a particular implementation of the example embodiments.

As shown in FIG. 3, a computing environment entitlement contract (CEEC) based resource management system 300 includes a transaction builder 312, a group and profile manager 314, a system Utilization manager 316 and CEEC manager 318 . A second web application server (WAS) 320 may include web services 322 - 326 including a market maker service 322 , group management service 324 , utilization scoring service 326 , and CEEC-based reservation service 328 . A database system 330 including a configuration management database 332 and a CEEC database 334 is provided. In addition, the database system 330 may include an interface 336 for interfacing with other organization or enterprise systems 340 (such as one or more human resource systems, etc.).

System 300 also includes an information technology management system 350 that includes one or more information technology management warehouse systems 352-356. Information technology management warehouse systems 352-356 collect utilization information from computing resources associated with the organization's various site systems 360-364. This computing resource utilization information collected by information technology management warehouse systems 352-356 can be used by web application services 322-328 to evaluate resource utilization (such as by utilizing scoring service 326), perform CEEC-based computing resource reservations (such as by utilizing CEEC reservation service 328), perform market-based exchange of CEECs (such as through market maker service 322) and perform group management with respect to groups of computing resources and groups of CEECs (such as through group management service 324), all These will be described in more detail below.

Database system 330 stores basic configuration information and CEECs of various computing resources of site systems 360-364 in CMDB 332 and CEEC database 334, along with resource utilization information obtained from information technology management warehouse 352-356 Used to perform various operations through the web application service 320 for ensuring compliance with CEEC, performing market transactions, performing group management, and scoring resource utilization. CMDB 332 may store, for example, various tables or other data structures of various types including, for example, daily resource utilization metric information, weekly resource utilization metric information, official resource utilization scores obtained from utilization scoring service 326, simplified file specifications, group specifications, group assignments, system configuration information, and system specifications for various computing resources. Available from Group and Profile Manager 314, Information Technology Monitoring Repository 352-356, Utilization Scoring Service 326, Group Management Service 324, and configuration scanning and discovery clients such as Tivoli Configuration Manager, Tivoli Application Dependency Discovery Manager, HP Open View, MS System Center Configuration Management Client, etc.) to obtain the information stored in CMDB332. A profile specification is an attribute of a profile that is used to interpret utilization data, for example, these are attributes such as whether optimal or running average data should be used, whether weekly or daily timescales should be used, should Consider how many days of history etc.

Information stored in CEEC database 334 may be obtained from user specifications of CEEC terms and standards specified via CEEC manager interface 318 . This information may also be augmented with information obtained from the group management service 324 identifying the group of CEECs with which the CEEC described in the CEEC database 334 is associated. In addition, a CEEC may be associated via CEEC database 334 with a particular identifier for a particular computing resource or group of computing resources. The content of CEEC will be described in more detail below.

The web application service 310 provides user-accessible web application services for performing various operations, including building exchanges via the transaction builder 312 for performing market-based CEECs via the market maker service 322, via groups and Transactions used in group and profile management by profile manager 314 , system utilization management via system utilization manager 316 , and CEEC management via CEEC manager 318 . The use of these various user-accessible web application services 310 will be described in more detail below.

Computing Environmental Entitlement Contract (CEEC)

The basic unit upon which the illustrative embodiments are built is the Computing Environment Entitlement Contract (CEEC). CEEC is an explicit agreement that a given party (for example, an individual, group, department, division, corporation, or other legal entity) will Computing resources (for example, hardware (CPU, RAM, disk IO, network IO, disk storage, etc.), software, physical infrastructure (heating, cooling, rack space, etc.) or a specific collection of services (governance, IT security, backup, etc.)) for a specified business purpose. CEEC can be specified in terms of one or more data structures that specify various terms of CEEC, including The CEEC characteristics outlined above. That is, one or more data structures specify the specific set of computing resources with which the CEEC is associated, either individually or in groups of computing resources as will be described below. The one or more data structures are also discussed below The specific hardware/software configuration of the designated computing resource that designates CEEC effective, the specific business purpose of CEEC, the given utilization level and pattern of intensity by quantifiable measures over a predetermined period of time, and unless due to failure to comply with CEEC's A CEEC required to be denied is valid for a given period of time. Additionally, one or more data structures may specify conditions for migration and/or denial of CEECs.

Figure 4 is an example diagram of an example CEEC data structure, according to an example embodiment. As shown in FIG. 4 , the CEEC data structure 400 includes a CEEC identifier field 410 for specifying the identity of the CEEC to which the CEEC data structure 400 corresponds. The CEEC identifier in field 410 is a unique identifier used to identify a CEEC when associating a CEEC with groups of other CEECs, groups of computing resources, and performing other management operations, including Migrate CEEC, deny and replace CEEC, etc. Essentially, the CEEC identifier is used as a way to uniquely distinguish a CEEC from other CEECs managed by the CEEC-based resource management system of an example embodiment.

The CEEC data structure 400 also includes a counterparty identifier field 420 that stores a counterparty identifier for uniquely identifying the counterparty or group of counterparties with which the CEEC is associated. For example, the contractor identifier in field 420 may be a unique employee identifier, department or workgroup identifier, user identifier, or the like. This contractor identifier can be used to correlate information from other enterprise systems (such as human resources systems, etc.) so that information from these other systems can be associated with the CEEC identified by CEEC data structure 400 . This contractor identifier may also be used, for example, to correlate utilization metric information and/or scoring metrics obtained from such utilization metric information to a particular contractor and corresponding CEEC.

The CEEC data structure 400 also includes one or more computing resource identifier fields 430 for uniquely identifying the computing resource, group of computing resources, or other groups of computing resources with which the CEEC is associated and their associated desired hardware/software configuration. That is, for example, computing resources of an organization's data network may be organized into groups as will be described below, and CEECs may be associated with the computing resource groups. Alternatively, CEECs may be associated with specific computing resources (eg, laptops, desktops, etc.). Specific configuration information may specify, for example, the number and type of processors, the amount of memory available, the amount of bandwidth available, specific software packages installed, or any other identifiable configuration element required to satisfy the business purpose for which the CEEC is established.

Additionally, CEEC data structure 400 also includes one or more fields 440 for identifying one or more specified business purposes for which the computing resource identified in field 430 may be used in accordance with CEEC. That is, projects, workgroups, departments, or other organizational divisions of an organization can be associated with identifiers for business purposes specific to those organizational divisions (for example, for software development, specific projects, accounting, management, human resources, etc. unique identifier) association. Specific computing resources can also be associated with these business purpose identifiers, for example, specific software packages can be associated with specific business purpose identifiers, for example, XYZ accounting software can be associated with a business purpose identifier corresponding to "Accounting", the word "XYZ" Process software may be associated with a business purpose identifier of "management," and so on. A particular computing resource, group of computing resources, etc. may be associated with more than one business purpose identifier. Additionally, a general business purpose identifier may also be provided for computing resources that are common across all business domains, eg, word processors, specific server computing devices, and the like. Field 440 may include business purpose identifiers with which the CEEC is associated such that the CEEC identifies for what business purpose the computing resource identified in field 430 may be used.

The CEEC data structure 400 also includes one or more fields 450 for specifying computing resource configuration requirements for meeting the terms of the CEEC and for a given period of time for which the contractor is required to utilize the computing resources specified in field 430 One or more fields 460 specifying a given utilization level and intensity mode. Utilization levels and intensity patterns can be specified in many different ways, but are generally intended to specify the amount of usage of the computing resource specified in field 430 that is required over a specified period of time in order for the contracting party to utilize the computing resource in accordance with CEEC terms and requirements . For example, field 460 may specify that computing resources need to be used for specified business purposes at least fifty percent of the time during the non-weekend 9:00 am to 5:00 pm hours in order for the contractor to comply with the terms of the CEEC. Utilization patterns can be defined in terms of exemplary systems that can describe daily, weekly, and monthly peak/valley heights and durations, as well as acceptable variations (eg, percent acceptable differences). For example, such patterns can be recorded numerically either directly or through a visual interface.

The CEEC data structure 400 may also optionally include a field 470 specifying migration criteria for migrating CEECs from a computing resource, group of computing resources, or the like. For example, field 470 may specify the types of computing resources to which CEEC data structure 400 may be migrated, ie, reassociated, the minimum requirements or configurations of those computing resources, specific conditions under which CEEC data structure 400 may be migrated, and the like. For example, a desktop workstation running x86CPU with 3G RAM and 500G local storage and running Windows Server 2008 acting as a departmental storage server can only be migrated to a visualization cluster running on x86 or x86-64CPU with no less than 3G of available memory. Additionally, the CEEC may specify, for example, that the watts consumed at the destination (weighted average) are no greater than 50, eg, as opposed to a desktop computer watt draw of 400.

The CEEC described by the CEEC data structure 400 is not an indivisible entity, but can instead be partitioned so that various computing resource providers can cooperate to provide the computing resources needed to satisfy the terms of the CEEC. That is, instead of two parties (ie, a single computing resource provider and a single contractor), CEEC can be established between three or more parties. So, for example, if one computing resource provider can meet a first subset of CEEC's terms (eg, processor throughput) and a second computing resource provider can meet a second subset of CEEC's terms (eg, storage capacity ), the CEEC can be divided into separate sub-CEECs, and a sub-CEEC is used for each clause of the original CEEC that must be separately satisfied by the separate computing resource provider. As will be described in more detail below, this allows for a greater chance for a successful transaction in the CEEC market, since no single "buyer" is required to be able to meet all the requirements for a CEEC "sold" via the CEEC market. This further distinguishes the CEEC mechanism of the illustrative embodiments from known workload management mechanisms, since such known workload management mechanisms typically move workloads as indivisible aggregate units.

The CEEC data structure 400 of an illustrative embodiment may be created by a system administrator or by an authorized user when another authorized user wishes to allocate one or more computing resources to a particular contractor. In other examples, as will be described in more detail below, CEEC data structure 400 may be created automatically by a CEEC-based resource management system, such as in response to determining that there is a need to deny an existing CEEC and replace the denied CEEC with a replacement CEEC. Assuming the authorized user is the user who created the CEEC data structure 400 , this CEEC data structure 400 may be created, for example, via a user interface such as may be provided by the CEEC manager 318 in FIG. 3 . Via this user interface, various lists of computing resources, groups of computing resources, contractor information, and user information can be presented to authorized users who can log in to the CEEC manager using a secure login process as is known in the art. Options to specify various other parameters of fields 410-470 of CEEC data structure 400. Information for populating such a list may be obtained, for example, from CMDB 332 , group management service 324 , utilization scoring service 326 , and/or other elements of system 300 in FIG. 3 . The resulting CEEC data structure 400 may be stored in the CEEC database 334 of FIG. 3 for later access by other elements of the system 300 for performing CEEC-based resource management operations as described below.

Accordingly, CEEC forms the basis by which resource management is performed in the system of the illustrative embodiments. CEEC differs from other computing resource arrangements in that it not only defines the obligation for computing resource providers to provide specific computing resources configured in a specific way, but also defines the contracting parties to use those computing resources for specific business purposes at specified utilization levels and intensity patterns. obligation. A known arrangement of computing resources sets an obligation on the provider to provide general computing resource capabilities (e.g., bandwidth, storage capacity, etc.), but does not identify specific computing resources and their specific configurations and, more importantly, does not specify any obligations on the part of the contractor. Take advantage of the request. On the contrary, the only obligation on the contractor is to make payment for computing resources, regardless of whether those computing resources are actually used by the contractor, regardless of the intensity level or pattern of usage of those computing resources, and regardless of the business purpose of the utilization.

Using the CEEC as a basis, the system 300 includes logic for operating on the CEEC to perform resource and contractor rights management. This logic provides mechanisms for enforcing the terms of the CEEC on both computing resource providers and contractors, including determining compliance with these terms, determining the need to deny and replace the CEEC, determining the need to withdraw from a group of CEECs and Migration of CEECs from one group of computing resources to another group of computing resources and/or to another group of computing resources and providing a market maker mechanism for facilitating denial, replacement and migration of CEECs. Additionally, this enforcement includes handling and routing workloads to appropriate computing resources (existing or planned) according to associations between CEECs and computing resources, such as through the grouping mechanism described below.

As an example of the CEEC and CEEC mechanism of the illustrative embodiment, assume that a particular organization has a business purpose of "DB2 performance testing". Also assume that in order to perform this DB2 performance test, a computing environment with 16 cores, 64G RAM, 10T bytes system running RHEL server 5.5, consuming 1500 watts, SAN with Gigabit Ethernet and fiber optic connections is required storage device, with 24/7 turn-on call supervision support. These terms are all terms that will be identified in the terms of CEEC. Any number of DB2 performance testing activities may be conducted on a computing system that meets these requirements under the terms of this CEEC, and the CEEC essentially defines a user's entitlement to a computing system's resources to perform activities on a computing system to implement a DB2 The purpose of the performance testing activity.

If the DB performance testing workload is to be migrated to a different computing system, the CEEC must be migrated first so that the user has confidence in the destination computing system. Destination computing systems include not only new or different assets (computing systems), but also new CEECs that ensure that all required elements of the computing environment will be provided as required under the CEEC. In addition, users are obligated to perform workloads related to DB2 performance testing in order to fulfill CEEC on their side, ie, providing users with computing environments in exchange for the output of business use (eg, DB2 performance testing).

Exemplary embodiments facilitate the migration effort by onboarding contractors into a new CEEC without which they would not have sufficient confidence to migrate and without which providers would not be fully notified The intensity and size of the upcoming workload as defined within the extended timescale. In addition, as described in more detail below, the CEEC market maker mechanism of the exemplary embodiments allows an organization or business to correctly price both sides of a transaction, which would not be possible if all that was considered was setting the computational effort of. That is, the cost of the existing environment can be priced, the cost of the destination environment can be priced, and the value of the business output can be priced. These prices can be compared with any or all of the alternatives to determine which migrations would be most beneficial.

Overview of CEEC Market Maker Mechanism

One of the main purposes of CEEC is to realize the valuation and buying and selling of rights to computing resources for optimizing the utilization of computing resources in organizations or enterprises, where optimization is defined as a process for realizing the utilization of computing resources owned by organizations or enterprises or multiple desired business objectives. This valuation allows for the creation of a CEEC market for valuing and buying and selling rights, however, this is not a free market. On the contrary, a CEEC market is a market that is owned by an organization or business and is designed and operated according to parameters and rules that are defined and designed to serve the interests of the organization/business. In a free market, any transaction that the parties to the transaction indicate to be a good deal (eg, the highest price for a particular product) is a good deal. However, in the CEEC market, an organization or business defines what is a good deal based on what benefits the organization or business goals the most rather than what benefits the parties to the transaction (ie, the buyers and sellers in the transaction) the most. Thus, organizations and businesses use market forces to ensure that its value is enhanced and realized through the dynamics of buying and selling.

Exemplary embodiments make it possible to value and increase the number of profitable transactions in the context of an organization or business, expressing its goals through market forces. This results in repudiation, replacement, and transfer of CEECs and their associated rights and obligations between groups of CEECs, groups of computing resources, contractors, etc., all for the ultimate benefit of the organization or business, which may sometimes compromise individual about parties, but such instances will be kept to a minimum.

For example, it may be necessary for an enterprise to migrate from a particular platform or to vacate a particular physical space or to deactivate a leased set of resources. These are three examples where a business may deny CEEC purely because its interests force such a denial. Holders of denied CEECs will be forced to enter the bazaar to discover buyers. Such buyers have had their CEECs denied through underutilization resulting in available capacity on the (enterprise) desired platform.

Workload migration is one of the outcomes of this CEEC market process. However, workload migration is not the ultimate goal of CEEC. The goal is to efficiently allocate rights to computing resources and resource utilization via market forces. This requires that all obligations, terms and considerations that are part of running a given computing environment (i.e. computing resources and their configuration) be encapsulated into a contract (i.e. CEEC) that defines what the parties can and must do for a known business purpose , the way of using the computing resources to which they have been allocated according to the terms of use, etc. The "workload" operates within the CEEC's parameters, and when a CEEC is migrated it can only do so by trading one CEEC for another according to any migration criteria that may be specified in the CEEC being migrated.

CEEC has value in static situations for ensuring proper use of assets, but the need for CEEC is in an attempt to move users (i.e., contractors) from one or more computing resources to another computing resource in an organization or enterprise ( For example, it is particularly urgent when moving from one hardware environment to another), where there are thousands of potential pairs in the organization or enterprise, and where there are many inhibitors to the free flow of workload. For example, as previously described above, users are often reluctant to trade their existing and potentially inefficient computing resources (e.g., laptops) that they are not fully utilizing in exchange for shared access to more efficient computing resources, regardless of current There are how computing resources may be underutilized because they lack confidence that shared computing resources will provide them with the full functionality they had with existing computing resources.

In short, employees may not be willing to give up a laptop they have commandeered and to which they have 100 percent rights in exchange for shared access to newer and more efficient computing resources (e.g., on servers, etc.), even though Even if the laptop is not used, because the employee has no subjective confidence that the computing resource will be as accessible to him/her as the laptop is currently, even if it is not utilized. That said, people tend to stick to the old adage "a bird in the hand is better than two in the bush" and tend to focus more on their immediate immediate needs than the overall best interests of the organization or business with respect to computing resources and their efficient allocation, e.g., " I know I need X amount of storage space for my projects, but I don't know or care what the people in the accounting department need for their projects".

In complex organizations, there are also many non-technical barriers to the flow of computing workloads that must contend with geographic scope, departmental budgets, and money-to-spend differences that make it difficult to buy a more efficient piece of hardware instead. Not running current inefficient hardware. Optimization is typically achieved through centralization and consolidation, but organizational boundaries often present obstacles to such activities. CEEC is the mechanism to achieve the removal of barriers.

Utilizing the mechanisms of the exemplary embodiments, CEEC market makers (such as CEEC market maker scope 322 in FIG. 3 ) allow contracting parties to trade their existing CEECs for new CEECs, which may include the Requirements (CPU, RAM, etc.) together with formal enumeration of all elements (network bandwidth, storage space, regulatory support, etc.). As long as the CEEC market maker can provide the contractors with information that will satisfy their utilization requirements, such as by having the necessary logic and facilities for both sides of the transaction to The enterprise's free inventory and occasional acquisition of slightly more than explicit requests to satisfy), still removes a key inhibitor to efficiently allocating computing resources. Furthermore, CEEC enables groups within an organization to contribute resources to a shared pool while still maintaining all rights to their existing resource claims through CEEC.

It should be noted again that the CEEC market maker mechanism of the exemplary embodiment does not operate as a neutral third party. Quite the contrary, they operate as driving forces for driving an organization or business in a specific direction, and they do so by creating and manipulating market forces that favor that specific direction. A CEEC market maker (eg, CEEC market maker service 322 has a specific intent expressed in the CEEC market maker's hardware/software logic for optimizing the efficiency of all utilization (workload) in a market (organization or enterprise). The specific way that the CEEC market maker mechanism is used to drive the market to achieve the operational goals of the organization or enterprise can be defined in a collection of the following CEEC market parameters, rules, etc. collectively referred to as "profiles". These CEEC market parameters, rules, etc. The CEEC market maker mechanism handles to control the selection of buyers, sellers, and pairing of buyers and sellers in the CEEC market and the creation, denial and replacement of CEECs via the CEEC market. Additionally, this can be done collectively with respect to computing resources and/or definitions of CEECs Done, this collective is referred to herein as a "group", and the criteria for defining such groups and their memberships are specified in the CMDB.

In the CEEC market, sellers and buyers do not decide to become sellers and buyers on their own. On the contrary, the CEEC market maker mechanism expressing the goals of an organization or enterprise applies profiles to utilization and configuration data to identify groups of computing resources and CEECs and to determine which units should be buyers and sellers. An application's profile is a collection of one or more parameters, rules, etc. that specify various aspects of the CEEC marketplace, including how and on what basis computing resources are grouped into groups ( The term "group" means a "collection" of similar units), how and on what basis CEECs are grouped into groups, how and when exploit information indicates the need to modify group membership, how and when certain exploit information Other parameters or rules that dictate when computing resources or groups should be considered buyers or sellers of CEEC and that dictate the manner in which the CEEC mechanisms of the illustrative embodiments perform or operate. A particular building block for facilitating CEEC market operations is, for example, a transaction that can be created automatically, manually, or using a combination of automated and manual processes (such as via transaction builder 312 in FIG. 3 ).

CEEC market makers can assemble transactions, but individual owners of buyer and seller systems can also proactively participate in transactions via the system utilization manager 316 . That is, while the transaction builder 312 allows planners, designers, and administrators to plan and/or document the migration of seller CEEC sets to buyers, the system utilization manager 316 allows individual users to specify their Sellers participate in the market within the context of individual systems. Additionally, where transaction builder 312 proposes migration sets, in some cases users of those systems will have to affirmatively accept invitations to participate in such transactions via system utilization manager 316 . Additionally, System Utilization Manager 316 is the mechanism by which users of a particular system are made aware of their CEEC obligations, enable the user to request a denial of CEEC by asserting different business usage, and enable the user to signal a willingness to engage in future transactions .

Since the CEEC market maker mechanisms of the exemplary embodiments govern all CEECs used in the CEEC market, these CEEC market maker mechanisms have the authority to revoke a CEEC when a party has failed to meet the CEEC's obligations. This provides incentives for contractors to utilize their allocated computing resources or discard those computing resources (i.e. become sellers) by using old hardware without justification or in a manner that does not match expectations as defined by CEEC Provided that the hardware is used in a manner that voids their contract. Thus, within the CEEC marketplace mechanism of an exemplary embodiment, sellers become sellers because they do not have a valid CEEC to use their allocated computing resource against the organization or business that owns it. Contract revocation also works on the buyer's side, where underutilized good new computing resources have their contracts rescinded, forcing them to buy additional workload from sellers by transferring CEECs and the resulting workload associated with those CEECs.

Workload Management Based on CEEC

The mechanisms of the illustrative embodiments operate on CEECs to facilitate the association of entitlements to computing resources specified in CEECs with the contractor's utilization of computing resources in anticipation, with the risk of revoking entitlements if the utilization does not meet minimum requirements. Workload management is enabled as a result of using the mechanisms of the illustrative embodiments to manage CEECs. Workloads are routed to computing resources and their utilization of computing resources is monitored according to the CEECs and their association with computing resources. Thus, when a particular contractor submits a workload, the CEEC associated with that contractor may be used as a basis for determining what computing resources to use to perform or otherwise perform the workload.

The workload management mechanism 380 in FIG. 3 can control workloads and route workloads to computing resources according to the CEEC associated with the particular contractor submitting the workload and the type of workload submitted. In an exemplary embodiment, upon receiving a workload from a contractor's computing device, one or more CEEC data structures associated with the contractor may be retrieved from the CEEC database, and the type of workload submitted may be determined , for example, storing workloads, processing workloads, etc. The type of business purpose associated with the retrieved one or more CEEC data structures can be determined and matched with the type of workload. As a result, a CEEC data structure is identified that relates to the same business purpose as that of the workload, and thus governs the type of computing resource that can handle the type of workload. The CEEC data structure can then be used to identify the corresponding computing resource governed by the CEEC data structure, and the workload management mechanism 380 can then route the workload to the computing resource specified in the CEEC data structure. For example, if submitting a workload for storing data to a storage system, then in the manner described herein (e.g., using group associations as described herein) is Association) The CEEC associated with the contracting party can be used to dictate where the workload is directed, ie to what computing resource the workload is sent.

Thus, although the example embodiments do not directly perform workload management, workload management is a beneficial result obtained with the CEEC-based mechanisms of the example embodiments. For example, a request for a new 'workstation' would be formulated as a request for CEECs to run a specified workload with a certain technical standard, with a specified utilization intensity pattern, (ie net new sold CEECs). This will be grouped based on intended business usage and matched with buyers with compatible capacity available.

group

As mentioned above, one way in which the market maker mechanism of the illustrative embodiment operates is through the group and profile manager 314 and/or the group management service 324 in FIG. Logic to generate and manage groups of computing resources and CEECs is applied to the computing resource utilization data, the terms and conditions information of the CEECs, and the configuration data of the computing resources and CEECs. As a result, groups can operate as buyers and/or sellers within the market maker mechanism of an example embodiment.

A group represents a collection of computing resources and/or CEECs that are similar in some definable way. For example, computing devices with the same or similar configuration, same or similar type, same or similar organizational assignment (e.g., associated with a particular site or location of the organization), physical location, logical location within the organization's or enterprise's data network, etc. Resources are grouped into same groups. Similarly, CEECs with the same or similar terms or subsets of terms can be combined into the same CEEC group, for example, CEECs that dominate storage capacity can be collected together in a group, and CEECs with organizations or enterprises can be grouped The CEECs associated with the parties in the same or similar division or department can be collected together, CEECs with the same or similar business purpose can be collected together in a group, and so on. A cluster analysis mechanism can be used to identify these similar computing resources and CEECs so that they can be combined into collections or groups of computing resources and CEECs.

For example, group management service 324 may analyze configuration information for computing resources stored in configuration management database 332 and CEEC terms and conditions identified in entries in CEEC database 334 and perform cluster analysis on this information to generate a Or multiple computing resource groups and one or more CEEC groups, where each group has members with similar characteristics to other members of the group. can be used in many different ways (e.g. same or similar (i.e. within defined tolerances) number of processors, same or similar amount of memory, same or similar software configuration, same or similar resource utilization requirements, same or similar business purpose, same or similar tissue locations) etc. to measure "similarity". As will be described below, specific rules and parameters for establishing a group are identified in the profile defining the group and may be recorded in the CMDB.

Once the computing resource groups are created and the CEEC groups are created, the group management service 324 may have functions for matching groups of CEECs (or simply "CEEC groups") to computing resources based on those computing resource groups The logic of one or more groups (referred to simply as "computing resource groups") that provide computing resources determined to be in the CEEC group necessary to satisfy the same or similar provisions of the CEEC. In this way, entitlement contracts associated with users can be associated in an automated fashion with one or more computing resources used to satisfy those contracts. Of course, group information and associations between groups can be exported to a system administrator or other authorized user via group and profile manager 314 so that the individual can review, cancel, modify, disregard, or Alter groups and their associations in other ways. The association of a CEEC group with one or more computing resource groups substantially reserves use of those computing resources, or at least a portion of those computing resources, by the CEECs in the CEEC group to the contractors in the CEEC group. Thus, once an association between a CEEC group and a computing resource group is made, the CEEC enforcement logic becomes operational.

Groups that are matched and related to each other in this manner may have their utilization monitored and analyzed in view of the association between groups. That is, computing resource utilization information may be collected, analyzed, and monitored for computing resources that are members of a computing resource group based on the terms and conditions specified in the CEEC of the CEEC group associated with the computing resource group. In essence, this information collection, analysis and monitoring is done to ensure that both the computing resource provider and the contractor (ie, the end user) comply with the terms and conditions of the CEEC. Thus, the collection of utilization information and its analysis and monitoring are performed with respect to the specific computing resource utilization terms specified in the CEECs of the CEEC group, but the collection is performed from the computing resources specified in the computing resource group with which the CEEC is associated. Thus, for example, if a CEEC specifies that users must dedicate 50% of their allocated processor time to running a software package involving accounting operations, then the collection of computing resources for the group of computing resources associated with this CEEC will be analyzed The processor utilizes the metric to determine whether the user runs the accounting software at least 50% of the time during the specified time period.

It should be appreciated that collecting computing resources and CEECs into groups need not be limited to aggregation based on computing resource configuration or CEEC terms and conditions as a whole. Rather, subsections of a CEEC may be individually assigned to different groups of CEECs, eg, based on the terms and conditions of the CEEC associated with that subsection. For example, the CEEC may specify terms associated with the allocation and utilization of processor resources, storage system resources, web application resources, and the like. Each of these terms can be satisfiable separately by different computing resources of an organization or enterprise, and thus can be separated into separate CEEC groups such that one CEEC can be associated with multiple CEEC groups and with separate CEEC groups Each of these associations may be separately managed by the mechanisms of the illustrative embodiments and may be separately the subject of CEEC market maker operations.

Group membership is not only based on similar terms in CEEC or similar configurations of computing resources, but can also be based on similar utilization metrics. That is, even though two computing resources may have similar configurations, and thus will generally be part of the same group, if their utilization metrics indicate that these computing resources are utilized in significantly different ways or at different levels or patterns of utilization intensity, then These two computing resources can be separately classifiable into different groups. This is also true for CEECs where utilization metrics associated with the CEEC can be used as a basis for determining whether the CEEC should be classified in a particular group. Utilization metrics may be obtained in any known manner (such as by using an agent application running as a daemon on the computing resource, probing the computing resource, etc.). Utilization metrics may be collected, for example, by data collection mechanisms (such as information technology monitoring warehouses 352 - 356 in FIG. 3 ) and analyzed to generate utilization information, such as a utilization score via utilization scoring service 326 . This utilization information can be associated with various computing resources and CEECs via database system 330 and can be used by group and profile management mechanisms such as group management service 324 to dynamically evaluate group membership and Use the changes in to readjust group membership. Similarly, changes in the configuration of computing resources may be identified and used via database system 330 as a basis for dynamically adjusting group membership when it is determined that it is necessary to optimize computing resource utilization for an organization or enterprise.

As will be described in more detail below, utilization scoring service 326 may operate on collected utilization metrics such as may be stored in configuration management database (CMDB) 332 and/or CEEC database 334 in relation to, as in profiles defining groups Metrics of interest and statistical representations of interest for a particular cohort are specified to generate scores for each member of the cohort. Also described below, these scores may be generated according to rules and parameters utilizing the logic of the score service and/or defined weights in the group's profile (these weights may be static weights or dynamically determined weights). The resulting score provides a relative measure of the utilization of the members of the group relative to other members of the group. This utilization can be compared to the desired utilization as specified in the terms of the CEEC with which the members of the computing resource group are associated to generate an indication of whether the computing resource is utilized according to the terms of the CEEC or whether the analyzed computing resource utilization satisfies the terms of the CEEC. always said. The resulting score can be used as a basis for adjusting membership in the cohort, denying, replacing and/or migrating CEECs, and the like.

For example, representations of these scores may be generated and presented to authorized users via the group and profile manager 314 . For example, a graphical representation of the CEEC's score for a CEEC group can be presented, such as in a multi-axis graph or the like, along with the scores of the computing resources of one or more computing resource groups with which the CEEC group is associated, such that the computing resource can be determined Which CEECs are satisfied by the utilization and which computing resources are used to satisfy the CEEC terms in the CEEC group. Various graphical representations can be used to aid in the visualization of this information, including utilizing color coding (eg, red/yellow/green) to further identify and provide compliance information and reporting on the terms and conditions of CEECs in the CEEC group. For example, such graphical representations may be provided on a per CEEC basis, on a CEEC group basis, or on an aggregated CEEC group basis.

FIG. 5 is a flowchart outlining example operations for generating associations of groups, according to an illustrative embodiment. The operations outlined in FIG. 5 may be performed, for example, by group management service 324 alone or, for example, in combination with group and profile manager 314 in FIG. 3 . It should be appreciated that FIG. 5 is an overview and that many details specific to particular implementations of the illustrative embodiments may not be explicitly shown in FIG. 5, but will readily become apparent to one of ordinary skill in the art in view of this description.

As shown in FIG. 5 , operations begin by defining one or more group profiles, at least one specifying a computing resource group and one specifying a CEEC group (operation 510 ). Comparing the computing resource configuration information in the database system with the CEEC information using the defined group profile to generate at least one computing resource group with one or more members and at least one CEEC group with at least one member (step 520) . Group memberships of CEECs and computing resources are noted and stored in the database system in association with entries for computing resources and CEECs (530). As mentioned above, it is possible for a single CEEC to be part of multiple CEEC groups, such as in the case of subdividing the terms and conditions of CEECs. Similarly, computing resources can be part of multiple computing resource groups by subdividing their configuration information into individual configuration item types. Thus, one CEEC group can be associated with multiple computing resource groups and vice versa.

Subsequently, the common or similar terms of the CEEC groups are compared to the common or similar configuration information for the computing resource groups to match one or more computing resource groups to one or more CEEC groups (step 540 ). Associations between groups are created and these associations may be stored for later use (step 550). Based on these associations, computing resources or portions of computing resources are reserved or allocated to CEECs in the associated group of CEECs (step 560).

Computing resource utilization metrics are collected from various computing resources and stored in a database system in raw form, as analyzed utilization information, or both (step 570). Analyzing computing resource utilization information in the database system based on group associations to determine whether contractors are in compliance with the terms and conditions of the CEEC in the CEEC group based on their utilization of computing resources in the computing resource group with which the CEEC is associated. condition (step 580). Based on the determination of compliance with the CEEC terms and conditions, a graphical representation of the compliance report may be generated (step 590) and group membership may be updated (step 595). The operation then terminates.

Accordingly, with the illustrative embodiments, mechanisms for reserving computing resources of a data processing system in a data processing system comprising at least one computing device and a plurality of computing resources are provided. These mechanisms may establish one or more Computing Environment Entitlement Contract (CEEC) data structures, each CEEC data structure defines the terms of a business level agreement between a contractor and a provider of computing resources for a data processing system, where the CEEC's A clause specifies a collection of computing resources with a specified configuration to be used by the parties for a specified purpose at a specified level and pattern of intensity for a specified period of time. These mechanisms may also associate a set of one or more computing resources with a set of one or more CEECs. Additionally, a mechanism may manage a set of one or more computing resources according to an associated set of one or more CEECs. In response to the failure of the contractor to utilize computing resources in the selected group of computing resources for the specified purpose approximately at the specified level and intensity pattern during the specified time period, the logic of the at least one computing device then causes the CEEC invalid. Such invalidation may result in replacement of a CEEC with another CEEC and/or migration of an invalid CEEC from one set of computing resources to another.

The relationship between resources, workload and CEEC can be very complex as described, but can also be very simple. It is important to note that simple CEECs can be traded into a much more complex environment. For example, a CEEC may require the use of a stand-alone desktop workstation for "basic office productivity" (email, word processing, etc.). This CEEC can be traded into a highly complex centralized virtualized cluster where the same business activities will be performed on a much more complex platform, but the cluster will not appear very different to the user and will behave as if The same method is used to accomplish the same thing on a stand-alone desktop. This underscores why CEEC is required to address this issue by moving from an environment where the user has full control to an environment where they have limited or no control and that they may not understand, can be run by people they do not know, in different geographically neutral environments They provide such confidence that their claims will be protected.

Associating the set of one or more computing resources with the set of one or more CEECs may include determining a first set of one or more computing resource groups of computing resources based on configuration information for each of the computing resources. Computing resources within a computing resource group may be of the same type and have configurations similar to each other. Associating may also include determining a second set of one or more CEEC groups of CEECs based on attributes of the one or more CEECs maintained by the data processing system, and based on the terms of the CEECs in the selected CEEC groups in the second set The selected CEEC group is matched with the selected computing resource group's characteristics with the selected computing resource group in the first set.

Managing the set of one or more computing resources according to the associated set of one or more CEECs may include enforcing the CEEC on the computing resources in the selected group of computing resources according to the terms of the CEEC in the selected group of computing resources. Enforcing a CEEC may include obtaining resource utilization metric information, determining compliance with CEEC provisions based on the computing resource utilization metric information, and determining whether to deny, replace, and/or remove from a CEEC group based on actual computing resource utilization when compared to provisions in the CEEC. A group migrates CEECs to another group of CEECs or from one group of computing resources to another group of computing resources.

Associate CEEC and groups with existing organization system information

CEECs, groups, etc. can be associated with existing organizational information such as employee information, department, division and location information, business units, etc. For example, database system 330 may include one or more organizational system interfaces 336 for interfacing database system 330 with these existing organizational systems to thereby obtain additional information and and/or link the CEEC, group and other data structures of the CEEC-based resource management system 300 with these existing organizational systems. In an exemplary embodiment, the contractors may be employees or departments of an organization or business, and the identifications for these employees or departments may be obtained from organizational systems 340, which may include employee directories, organization configuration systems, human resources systems, etc. information.

Information obtained from existing organizational systems 340 may be used by database system 330 to populate fields in entries in CEEC database 334 and/or CMDB 232 to thereby correlate information from these other organizational systems 340 with CEECs and computing resources and groups thereof . For example, a CEEC can be assigned to a particular employee and the employee's information can be automatically retrieved from an existing organizational system 340 (e.g., a human resources system) and used to populate the fields of a CEEC database 334 entry for the CEEC, e.g., employee Identification number, name, department, business unit, etc. Similarly, the existing organization system 340 can be updated to link information from the database system with entries for the contractor, e.g., an identifier of the CEEC associated with the employee, a group of computing resources associated with the CEEC associated with the employee. identifier, etc.

Additionally, information obtained from existing organization system 340 may be used by group management service 324 and group and profile manager 314 to assist in identifying members of a group, ie, to assist in generating a group. For example, profiles can be generated for particular business units, departments, or other organizational units within an organization or enterprise, and information obtained from these existing organizational systems 340 can be used to generate these profiles and populate corresponding groups.

As another example of the manner in which these organizational systems 340 may be used to assist in the creation and management of groups, computing resource utilization information may be obtained and analyzed for various groups to identify trends and patterns of utilization under CEECs associated with computing resources , and organizational information from organizational system 340 may be used to identify other contracting entities, business units, etc. that may be associated with other groups having similar utilization trends or patterns to generate resulting reports. This information can then be used to determine group membership among such organizational entities (eg, employees, business units, departments, etc.).

profile

Profiles used to define groups may be provided by a system administrator or otherwise authorized via, for example, one or more user interfaces provided by group and profile manager 314 in FIG. 3 alone or in cooperation with the logic of group management service 324. personal definition. Profiles can be generated for use in defining various computing resources and/or CEEC groups. A profile specifies parameters used to define a group and what computing resources/CEECs can be members of the defined group. A profile may specify which utilization metrics are evaluated to determine membership in a group and what utilization levels and/or patterns associated with those metrics indicate membership in the group, removal from the group, and the like. As mentioned below, these utilization levels and/or patterns for adjusting membership in a group may be dynamically determined based on utilization information gathered, for example, by selecting exemplary and de-exemplary members of the group.

Profiles may be applied to computing resource configuration information (eg, as available from CMDB 332 ) and CEEC data (eg, as available from CEEC database 334 ), both of which may store utilization information corresponding to one or more metrics , regardless of whether this utilization information is raw metric data or the result of processing raw metric data, eg, utilization scores, etc. Profiles can be applied to computing resource configuration information and CEEC data to identify which computing resources and which CEECs should be members of corresponding groups. Database system 330 may be updated accordingly to include an identifier for the particular computing resource and the group with which the CEEC is associated.

Profiles can be defined in many different ways depending on the particular implementation. Preferably, as shown in FIG. 6 , the profile 600 includes a unique identifier 610 of the profile, characteristics or terms of computing resources of the CEEC 620 indicating membership in a group corresponding to the profile, Identification of specific utilization metrics 630 used to evaluate membership in the corresponding cohort, criteria 640 for evaluating those metrics, and criteria 650 for determining when to adjust membership in the corresponding cohort and associated with these adjustment criteria The corresponding action 655 of and other parameters and rules of the profile 660. Criteria 640 for evaluating metrics for use in determining membership in groups may include, for example, the time frame over which the evaluation was performed, the basis for measurement utilization (e.g., maximum, minimum, average, etc.), Basis of evaluation (e.g. best, worst, latest, running average, etc.), etc.

Adjustment criteria 650 and corresponding actions 655 may, for example, specify a range of metric utilization information that will cause a particular action to need to occur. These actions 655 can be CEEC market maker actions, such as buy, sell, hold or delist, where buy refers to adding more CEEC to a computing resource or group, and sell refers to migrating from a computing resource or group Out of CEEC, keep means no action is taken, and decommissioning means permanently decommissioning a computing resource or group so that it is not reused or otherwise denying CEEC/CEEC group. Accordingly, the CEEC market maker service 322 may utilize profiles as a mechanism for assisting in selecting buyers and sellers within the CEEC marketplace associated by the CEEC market maker service 322 .

Group management service 324 may store profiles 600 generated by system administrators or other authorized users so that they may be applied to computing resource configuration information in CMDB 332 and CEEC terms and conditions specified in CEECs stored in CEEC database 334 condition. Initially, at system initialization, when new computing resources are added to the system, or when new CEECs are created, none of the utilization information in database system 330 will be used to determine The basis for membership in . Accordingly, membership in a group can be initially determined based on the computing resource configuration information and CEEC terms/conditions specified in the database system 330 . Subsequently, as computing resources are utilized under the various CEECs, utilization information may be collected/generated and used as a basis for dynamically adjusting in the various groups defined by these profiles 600 according to the adjustment criteria specified in the profiles 600 basis of computing resources and membership of CEEC. Accordingly, group management service 324 may continuously or periodically monitor the profile and apply the profile to information stored in database system 330 to determine adjustments to group membership.

Profiles 600 created and managed via group and profile manager 314 and stored in association with group management service 324 may be updated by authorized users through one or more user interfaces provided via group and profile manager 314 . Additionally, as will be described below, these profiles 600 can be dynamically updated based on analysis of utilization metrics for members of the group, for example, selecting different utilization metrics or different weightings for distributions based on utilization metrics, representative Evaluate group operations based on specific group membership, identification of outsiders, etc. In response to updating these profiles 600, the group management service 324 may apply the updated profiles 600 to the existing members of the group to determine whether the membership and database system 330 should be maintained or modified for other computing resources and/or Or configuration information and CEEC information of CEECs, these other computing resources and/or CEECs may be candidates for inclusion in the group in view of the updated profile 600 .

Use Profiles to Score Utilization Information to Manage Groups

As mentioned above, profile 600 may specify computing resource utilization information used to evaluate utilization by group members. Each member of the group is evaluated according to the same profile 600 that defines the group. Such evaluation may be performed by the group management server 325 alone or in combination with the group and profile manager 314, for example, automatically or with manual intervention by an authorized user. Evaluation may be performed based on the rules, parameters, etc. specified in profile 600 when applying them to computing resource utilization information available from database system 330 , which may include utilization scores generated by utilization scoring service 326 .

For example, profile 600 may indicate that for a particular group, the most important utilization information to be used to evaluate members of the group may be storage capacity metrics, processor cycle statistics, average number of processes executing over a predetermined period of time, etc. . This computing resource utilization information may be obtained from database system 330 and/or utilization scoring service 326, for example. Utilization information may be used to "score" members of a group and/or the group as a whole according to scoring rules and weightings. Such scoring can be accomplished, for example, by utilization scoring service 326 in FIG. 3 . The resulting scores can be categorized into predefined resource utilization score categories that indicate the relative utilization of computing resources under the associated CEECs of the CEEC groups for which utilization scoring is desired, e.g., scores can be categorized as "green", " "Yellow" and "Red" categories that indicate whether the resource utilization is in the range that indicates that computing resources are used in accordance with the CEEC provisions, within the acceptable tolerances of the CEEC provisions, or not within the acceptable tolerances of the CEEC provisions, or group. When updating profile 600, members of the group and/or other computing resources/CEECs that may become members of the group may be similarly updated based on any changed resource utilization information parameters, weights, etc. in the updated profile. score.

For example, the basis for classification could be green (indicating that no further utilization of this set of resources can reasonably be expected), red (these resources are not being used) and yellow (utilization somewhere between the thresholds defining red and green classifications) . These classifications may in turn be associated with corresponding actions expected to be performed, which may include denying a CEEC, replacing a CEEC, migrating a CEEC, and the like.

For example, a profile for a CEEC group may specify evaluation criteria for evaluating computing resource utilization under the group's CEEC (keeping in mind also that members of the group are evaluated against the same profile as defined for the specified group). These evaluation criteria can include measurement basis (e.g., minimum, maximum, average, variability, etc.), time scale (e.g., hourly, daily, per week), scoring period (eg, number of days considered), and any scoring preference (eg, best, running average, newest). These evaluation criteria specify how the computing resource utilization metric measurements will be interpreted and processed to derive a single score indicating how the computing resource utilization and the terms and conditions of the CEECs for the CEEC cohort measure. These evaluation criteria can be set according to the business goals of the organization or enterprise to determine how computing resource utilization data will be interpreted and applied to the determination of whether the contracting parties and computing resource providers comply with CEEC provisions.

Assessments may be used directly or aggregated, meaning that acceptable utilization patterns may be discernible within a given timescale, or within a collection of multiple instances of a given timescale, etc. For example, an assessment may be performed with respect to acceptable utilization of at least one day a week over a period of the past six weeks.

The scoring operations performed by utilizing the scoring service 326 can be performed in various ways based on the evaluation criteria specified in the profile for the group. The specific function or mathematical algorithm used to generate the score is not the focus of the present invention, and any suitable function or mathematical algorithm that can utilize the evaluation criteria specified in the profile and generate a single unified score for CEEC and/or computing resources is intended to be used in the exemplary within the spirit and scope of the exemplary embodiments.

In some demonstrative embodiments, these functions and/or mathematical algorithms may utilize weighting applied to various ones of the computing resource utilization metrics and/or evaluation criteria specified in the profile. These weights may be fixed and predetermined, eg CPU usage has a weight of 1.0 and storage capacity utilization has a weight of 1.25 and average weekly bandwidth utilization has a weight of 2.15. These weights can be set to any desired value to achieve an organization's or enterprise's business goals with respect to CEEC and computing resource management.

Alternatively, these weights may be determined dynamically and may be specific to a particular profile and group such that different profiles and groups may use different weights for the same computing resource utilization metric. These dynamically determined weights may also be determined based on statistical analysis of computing resource utilization metrics collected for computing resources of computing resource groups of the CEEC group with which the CEECs of the CEEC group are associated. That is, statistical analysis of computing resource utilization metrics for computing resources may indicate that a particular computing resource (e.g., CPU capacity, storage capacity, memory capacity, bandwidth, etc.) tends to be more efficient when compared to other computing resources in the group. Indicates the actual relative utilization of the computing resource and may further indicate whether the computing resource is utilized in terms of the CEEC with which the computing resource group is associated, and thus may be relative to the profile with respect to the computing resource group being used for this CEEC group Other computing resource utilization metrics monitored below dynamically increase the weight of this computing resource utilization metric. Accordingly, statistical analysis of computing resource utilization metrics can be used as a basis for determining dynamic weighting of computing resource utilization metrics when generating scores for computing resources, computing resource groups, CEECs, or groups of CEECs.

In addition, the weighted ratio enables detection of utilization patterns that are not expected for the assigned group or are expected for some other group. In some cases, going outside of the ratio utilization pattern (such as 100% CPU utilization combined with low RAM utilization) indicates a system problem. Thresholds defined in the profile determine how such exploitation should be interpreted in the context of the group.

Weighting may be used as a mechanism for allowing a profile to be matched to a deterministic limit of computing resources of the group defined by the profile. Thus, for example, for computing resources whose utilization is primarily limited by the amount of available memory resources, the weighting for the memory resources may be heavier than for other groups of computing resources in which the memory resources are not so limited. Thus, the weights are customizable within each profile so that they can be set appropriately for a particular set of computing resources and CEECs comprising the group defined by the profile.

In view of the foregoing, it can be appreciated that the illustrative embodiments provide mechanisms for monitoring usage of computing resources relative to computing environment rights contracts in a data processing system including at least one computing device and a plurality of computing resources. These mechanisms establish one or more Computing Environment Entitlement Contract (CEEC) data structures, each CEEC data structure defines the terms of a business level agreement between the parties to the data processing system and the provider, where the terms of the CEEC specify that the A collection of computing resources with a specified configuration used by a contractor for a specified purpose at a specified level and pattern of intensity for a specified period of time. These mechanisms also generate a CEEC group that includes a collection of CEECs with similar terms and a collection of computing resources with characteristics that satisfy similar terms for the CEECs in the collection of CEECs. In addition, these mechanisms collect within one or more pools or groups of computing resources resource utilization metrics that measure the amount of usage of each computing resource in the pool of computing resources according to similar terms of the CEEC pooling. Additionally, the mechanisms of the illustrative embodiments determine relative weightings of resource utilization metrics for various ones of the computing resources in the computing resource pool based on the business goals defined for the CEEC group. In addition, the mechanisms of the illustrative embodiments report CEEC group utilization of aggregates of computing resources based on collected resource utilization metrics and determined relative weights of resource utilization metrics.

7 is a flowchart outlining example operations for generating a computing resource utilization score, according to an illustrative embodiment. The operations outlined in FIG. 7 may be performed, for example, by utilization scoring service 326 when scoring utilization metrics for computing resources and/or computing resources in a CEEC group.

As shown in FIG. 7 , operations begin with the utilization scoring service 326 retrieving a profile for the group that is the subject of the utilization scoring operation (step 710 ). Evaluation metrics and evaluation criteria information for the group are extracted from the retrieved profiles (step 720 ), and utilization metric information for computing resources associated with the group is retrieved or collected (step 730 ). This retrieval may be, for example, retrieval of utilization metric data from database system 330 if the data has already been collected from information technology management systems 352-356, or may be the The actual collection of utilization metrics data.

Weighting to apply to the retrieved/collected evaluation utilization metrics is determined (step 740). This can be done by retrieving static predefined weights that can be specified in profile 600, for example. Alternatively, weightings may be determined dynamically by analyzing trends and statistics from utilization metrics previously collected and analyzed for this particular group. Where weights are determined dynamically, these weights may likewise be stored in fields of profile 600 for retrieval by utilization scoring service 326, but may be dynamically updated. Regardless of the particular implementation, the weights are specific to the group being scored, and other weights for other groups may differ from the weights for the current group for the same utilization metric type or for other utilization metric types.

Weights are applied to the corresponding utilization metrics (step 750), and scores are calculated based on the weighted utilization metrics and the evaluation criteria specified in the group profile 600 (step 760). As mentioned above, the evaluation criteria may specify various criteria for calculating the weighted utilization metric, including the period over which the evaluation is made, the basis on which the evaluation is made (e.g., maximum, minimum, average, etc.) , preferences for such evaluation (eg, best, worst, newest, running average, etc.), etc. These may use one or more mathematical algorithms or formulas to be applied with weighting to the utilization metric to generate a single score for the group or for the members of the group. Scores, etc. may be determined directly within a timescale or aggregated for each timescale within a term, eg, the latest daily score or the daily score for each day in the period, etc.

The score is then compared to one or more thresholds to classify the utilization of the group as to whether the utilization complies with the utilization requirements of the group (step 770 ). Scores generated in this manner may be stored in association with an entry in a database system corresponding to a group (step 775), and as to whether the classification of utilization based on the score indicates that a group management action needs to be performed and what action should be performed based on the classification A determination is made (step 780). These group management operations may be, for example, buying, selling, maintaining, or canceling CEECs associated with the group, issuing tickets for adding additional computing resources to the group, issuing tickets for parking computing resources associated with the group, etc. used tickets etc. A determined group management action may then be initiated (eg, via the CEEC market maker service 332 ) (step 790 ), for example, and the operation terminated.

Select model members for group

In addition to the above, scoring performed by utilization scoring service 326 from profile 600 and computing resource utilization information may also be used as a basis for selecting one or more exemplary members of a group. For example, a list of members of a group may be provided, the list rows sorted by score, and exemplary members of the group may then be selected from the list, e.g., members representing the mean The member with the closest score to the total score etc. A model member (typically a member of a group that has computing resource utilization that is considered good/acceptable and achievable within the business context) is used to describe acceptable usage boundaries for other members of the group. Exemplary members may be selected automatically by the group management service 324 using selection criteria and an ordered member list or manually via the group and profile manager 314 using a graphical user interface via which the ordered members may be presented to the user list and the user can select model members from the list.

Similarly, counter-model members can be selected automatically or manually in a similar manner. Counter-exemplary members of the group are preferably selected from members of the group that are not used within the business context, eg computer resource utilization information in the "red" category is used to describe unused boundaries for other members of the group. Such a counter-model defines the group's 'noise floor', the maximum amount of background or baseline activity to be considered 'unused'. For example, in the case of RAM, a counter-example defines the amount of RAM needed to load an OS, but nothing else.

Exemplary and anti-exemplary members of a group may be used as a basis for setting boundaries in a profile 600 corresponding to a group, e.g., criteria 650 for determining when to adjust membership in a corresponding group and related to these adjustments. Corresponding action 655 for standard association. Thus, for example, based on particular utilization information important to a particular group, a statistical representation of the actual utilization information collected for members of the group can be generated, e.g., a distribution of utilization information for a metric of interest can be generated for a group, Normalized curve or other statistical representation. This statistical representation may be based on weights provided to the various elements of the utilization metric, such as those discussed above, where the weights are predetermined or determined dynamically. Additionally, statistical representations can be generated based on utilization information obtained over a specific time period, and thus can represent trends in computing resource utilization behavior within a group over time.

The resulting statistical representation may be analyzed by the group management service 324 to automatically identify exemplary and non-exemplary members of the group for use in setting upper and lower bounds on computing resource utilization for accounting for membership in the group. Alternatively or additionally, a graphical output of statistical representations may be generated and presented to authorized users via group and profile manager 314 so that authorized users may select model and de-model members or not be considered by group management service 324 automatic selection.

Furthermore, the generation of statistical representations of resource utilization information and the analysis thereof performed by the group management service 324 may be used as a way of comparing groups with each other. That is, the trends (patterns) and statistical representations of one cohort can be compared to those of other cohorts to determine which cohorts have similar resource utilization trends. These similar groups can be logically linked within the group management service 324 so that when group membership needs to be modified, the logically linked groups can be checked first to determine whether members of a group should be joined to the logically linked groups. Group transfer. In this way, a sort of "link list" approach can be used by first searching for groups that are directly logically linked to the first group, and then continuing to search for groups that are logically linked to the first group. Those groups and so on are searched for new groups to which members expelled from the first group are transferred. Such group reassignment may be done based on cost and/or value, particularly when groups with similar utilization patterns or trends have significantly different costs.

Statistical representations or other analysis of resource utilization information may also be used to determine members of a group that are outliers and should be expelled from the group. That is, members of the group may be identified as outliers and candidates for expulsion from the group with scores or computer resource utilization information indicating that they differ significantly from the group's exemplary Or counter-exemplary membership (where significantly different can be determined, for example, based on a predetermined threshold). Expulsion causes the member to no longer be associated with the group, and thus not included in future expulsions of the group, but also associates the member with another, more appropriate group via the market maker mechanism as described below. In essence, eviction makes the current group a seller of CEECs or computing resources, while other groups operate as potential buyers of CEECs or computing resources. The selection of buyers and sellers and the use of market power in CEEC based on market maker mechanisms (such as CEEC market maker service 322) will be described in more detail below.

8 is a flowchart outlining example operations for selecting exemplary and de-exemplary members of a group and using this selection to define evaluation criteria and associated actions in a profile, according to an illustrative embodiment. The operations outlined in FIG. 8 may be implemented, for example, by utilizing the scoring service 326 in conjunction with the group management service 324 .

As shown in FIG. 8 , operations begin by obtaining utilization scores for members of a group, which may be computing resources or CEECs (step 810 ). An ordered list or other ordered arrangement of the members of the group ordered according to the scores associated with the members is generated (step 820 ). Exemplary members of the group are selected from the ordered membership ranking based on exemplary selection criteria (eg, mean, closest to mean score, etc.) (step 830 ). Counter-exemplary members of the group are selected from the ordered membership ranking based on counter-example selection criteria (eg, furthest score from mean, largest or lowest score, etc.) (step 840 ). Utilization boundaries are set based on the exemplary member's utilization metrics, eg, thresholds and utilization ranges or score ranges and associated actions for the group (step 850 ). The operation then terminates.

Computing resource reservation based on CEEC and group association

Based on the established group and its association, various ones of the computing resources of the group are reserved for use by the contractors of the CEECs in the group of CEECs associated with the group of computing resources. The CEEC-based reservation service 328 includes logic, as described below, for performing such reservations within an organization or enterprise system and removing reservations for computing resources, such as part of the transaction settlement phase of a transaction. Such reservations may include creating user accounts, migrating user accounts, generating requisition tickets for requisitioning computing resources (e.g., laptops, desktops, etc.) The contracting party recycles unused or underutilized laptops, desktops, etc.) to generate recycling coupons, etc.

Reserving computing resources may also include monitoring the total number of computing resources of the computing resource group subject to entitlements specified in the CEEC of the CEEC group associated with the computing resource group to determine whether and how much computing resources are available for use by the same or different Other CEECs of the CEEC group are reserved. For example, it may be determined that the CEEC of the CEEC group associated with the computing resource group currently represents 90% of the reserved CPU computing resources of the computing resource group. Based on the established computing resource reservation threshold, this reserved amount of computing resources can be compared to the threshold to determine whether additional CEECs can be accommodated, and can be used in determining group management operations such as associating CEECs with groups, associating computing resources with groups , migrating CEECs between cohorts, etc.) such a determination is used. Additionally, such comparisons to thresholds can be used as a means of generating alerts or notifications to system administrators or other authorized users of the need to add additional computing resources to an organization or enterprise in order to increase the number of available computing resources that can be used in connection with CEECs. Way.

Thus, based on generating CEECs, generating profiles, generating groups based on these profiles, and associating groups of CEECs with groups of computing resources, computing resources can be reserved for use by contractors of these CEECs. Additionally, CEECs may be informed as to whether sufficient computing resources are available to support the computing resources associated with a CEEC to a group, whether migrating a CEEC is appropriate, and/or notifying a system administrator or other authorized individual of the need to add additional computing resources to support a CEEC group. And where (ie, what group of computing resources) such addition is appropriate is determined.

In addition, when computing resources are no longer associated with a particular CEEC, the CEEC's reservation to those computing resources can be removed. In some instances, when migrating a CEEC from a computing resource that needs to be decommissioned, the CEEC-based reservation service 328 can generate and issue a command for a system administrator or other authorized user to remove a computing resource from a useful state in the organization/enterprise. Work tickets or notifications for resources, which in the case of physical hardware devices may require reconfiguration of organizational/enterprise systems to remove physical hardware devices, thereby physically decoupling hardware devices, removing and decommissioning physical hardware devices. This may be the case, for example, in scenarios where CEECs are migrated from older, potentially obsolete computing resources that are either unutilized, underutilized, or used in conjunction with them, and to newer, potentially more efficient computing resources. A different purpose than the intended purpose as specified in the CEEC.

Determining CEEC Compliance

Using the mechanisms described above, the CEEC-based market maker system 300 of the illustrative embodiments can determine when counterparties are using computing resources in accordance with the CEECs associated with those counterparties. Specifically, the logic provided in the CEEC-based market maker system 300 may operate on groups of CEECs to determine whether a contractor's utilization of a computing resource in a group of computing resources associated with a CEEC in the group of CEECs is Meet the terms of those CEEC. Computing resource utilization metric information obtained from information technology monitoring system 350 and stored in database system 330 and scoring information obtained from utilization scoring service 326 can be used to determine whether the specified usage specified in the CEEC of the CEEC group is met Such a manner is required to use those computing resources in the computing resource group.

As an example, assume for simplicity of this example that a group of CEECs includes a single CEEC and that this group of CEECs is associated with a single group of computing resources that includes multiple computing resources. The association between CEEC groups and computing resource groups may be performed according to mechanisms as discussed above. Periodically, continuously, or in response to an event (such as a system administrator or authorized user requesting a CEEC compliance determination), CEEC compliance operations may be performed by CEEC manager 318 on CEECs identified in CEEC database 334 . As a result of CEEC compliance operations, compliance reports can be generated and output to a system administrator or other authorized user and adjustments to CEEC groups can be initiated.

A CEEC compliance operation may determine for a CEEC of a CEEC group (or for each CEEC in a CEEC group in the example of multiple CEECs in a CEEC group) the minimum utilization requirements specified in the CEEC's terms and conditions, e.g. 50% of the average daily CPU usage involves running accounting software. Based on the profile associated with the CEEC group, the CEEC compliant operations may obtain computing resource utilization information from computing resource metric information collected for specific computing resources of the computing resource group with which the CEEC group is associated. For example, if a CEEC group is associated with a computing resource group that corresponds to a particular type of processor, number of cores, speed, etc., as may be specified in the CEEC group's profile, and the CEEC group's If the profile indicates that the resource utilization assessment should be performed in terms of peak number of processor cycles per minute, computing resource information may be determined based on peak number of processor cycles per minute information collected for processors in the computing resource group. This information may be correlated with information indicating what process was performed during periods of these peak numbers. From this one can approximate how much time and how many processor cycles of computing resources are dedicated to performing various processes.

The specificity of this scrutiny may vary according to the cost of CEEC. For example, the most expensive CEECs can be assessed at this process level, while the least expensive CEECs can be more simply measured on an average general utilization basis. In the latter case, the compliance check simply determines whether the weighted combined utilization score is above a threshold. Any degree of specificity between the two extremes can be supported.

Based on this computing resource utilization information and the evaluation criteria specified in the CEEC group's profile, a determination is made as to whether at least 50% of daily CPU usage involves running accounting software. Thus, for example, based on computing resource utilization information, a total peak number of periods dedicated to running an accounting software process can be determined as distinct from other types of processes. From this an average or other evaluation criterion specified value can be generated over a specified period of time (eg, days). This one value may then be compared to the minimum requirements specified in the terms and conditions of the CEEC to determine whether the contractor's use of computing resources in the group of computing resources with which the CEEC is associated complies with the CEEC.

Compliance can be determined based on strict or flexible compliance criteria. Strict compliance requires that specific clauses in the CEEC be met otherwise non-compliance with the CEEC is determined. Flexible compliance allows for a tolerance around the terms of the CEEC within which it would still be considered CEEC compliant, but could be flagged for additional monitoring, for example. Thus, if a CEEC is flagged for additional monitoring, events for initiated CEEC compliant operations may be scheduled at increased frequency, for example. Based on determining whether compliance with the CEEC terms and conditions is strict or flexible, an indication of the degree of compliance may be generated and used, along with the actions defined in the profile associated with the CEEC group's profile, to determine the appropriate action to perform Foundation. For example, as previously mentioned above, a graphical representation, such as a multi-axis graph, etc., can be generated that identifies compliance with CEEC, such as by color coding, etc., whether CEEC is within strict compliance tolerances, but needs to be further monitored, or Whether CEEC is not complied with. This graphical representation can be output to a system administrator or other authorized user so that they can make decisions about how to modify CEECs, associations of groups, etc. to achieve the business goals of the organization or enterprise.

This can also be dictated by the willingness and/or ability of the business to handle migration. For example, if a business can only move 100 CEECs a month, then identifying 10,000 CEECs won't matter. Therefore, thresholds are defined initially as 'loose', so that only the least compliant CEECs are identified, and can then be more tightly defined as progress progresses.

In addition, the CEEC market maker service 322 may be used to automatically initiate actions specified in profiles for CEEC groups corresponding to various levels of compliance. These actions could be, for example, sell, keep or eliminate. For example, if the degree of compliance shows that the CEEC is being complied with or is within strict compliance tolerances, then a hold action can be performed, where migration on the CEEC is not done, and thus the CEEC remains part of the CEEC group, and the CEEC group remains Associated with one or more computing resource groups. If the level of compliance shows that the CEEC is not being complied with, but there is some exploitation under the terms of the CEEC, a sell action can be initiated to have the CEEC disowned and replaced with a new CEEC with new terms corresponding to the actual utilization and/or to another One or more computing resource groups migrate CEECs or replace CEECs. If the degree of compliance shows no utilization of the terms on the CEEC, the action may be to eliminate the CEEC without replacing the CEEC.

It should be appreciated that similar compliance determinations may be made with respect to compliance of computing resource utilization with utilization requirements specified in a profile defining a group of computing resources. Such compliance determinations are typically made to determine whether the utilization of a group of computing resources indicates that the group has sufficient resources available to call a "buy-in" basis for additional CEECs, sufficient use of the group's resources to call a contribution to another group of computing resources. The basis for "selling" a CEEC is either to utilize group resources at an efficient level such that no changes should be made, ie a "hold" action should be performed. Therefore, computing resource groups can be designated as buyers or sellers in the CEEC market, where the financial unit in the CEEC market is CEEC, that is, computing resource groups are buyers or sellers of CEEC, and whether they are buyers or sellers The determination of can be based on computing resource utilization analysis and compliance with CEEC terms and conditions.

The transaction builder 312 can be used via the CEEC market maker service 322 to perform certain actions that are subject to operational identification via the CEEC. That is, transactions can be created for buying or selling CEEC. The CEEC market maker service 322 may process transactions by pairing buyers and sellers according to the rules and parameters specified in the CEEC market maker service 322 to achieve the organization's or enterprise's business goals. These rules or parameters, together with evaluation criteria and CEEC compliance determinations, essentially define market forces for migrating and associating CEECs via CEEC groups with computing resources via computing resource groups. The actual operation of the CEEC market maker service 322 will be described in more detail below.

FIG. 9 is a flowchart outlining example operations for assessing CEEC compliance, according to an illustrative embodiment. As shown in Figure 9, operations begin by identifying CEEC terms for the CEEC being assessed for compliance (step 910). Computing resource utilization information is collected from the group of computing resources with which the CEEC is associated (step 920). A determination is made as to whether the computing resource utilization information indicates that the computing resource is used in compliance with the terms of the CEEC (step 930 ). If so, a "keep" action is performed so that no changes in the CEEC group or computing resource group are performed (step 940). If the computing resource utilization information indicates that the CEEC terms are not being complied with, a "sell" action may be performed to cause the group of computing resources corresponding to the group of CEECs to become sellers of CEECs in the CEEC market maker system (step 950 ). If the computing resource utilization information indicates that groups of computing resources have sufficient resources to accept additional CEECs (step 960), these groups of computing resources may become buyers in the CEEC market maker system (step 970). The operation then terminates.

Thus, via CEEC compliance operations, a determination can be made as to whether not only the computing resource provider providing the required resource under CEEC satisfies the terms of the CEEC but also whether the contractor complies with the terms of the CEEC. If the CEEC terms are not met by the contractor, the CEEC may be migrated to another computing resource group, denied and replaced with a new CEEC in the same or a different CEEC group associated with the same or a different computing resource group, or if desired are simply eliminated without replacement. This in effect enforces the terms of CEEC on computing resources and contractors.

Denied CEECs are not all equal. This is why it is important that they can be priced so that businesses can prioritize the CEECs that cost the most, are the most valuable, or are the easiest to save.

Furthermore, a business, via the CEEC market maker described below, has the ability to deny CEEC on any other basis to serve its short or long term purpose. Such a denial does not take into account any automated CEEC compliance assessment. Therefore, enterprises cannot deny CEEC for systems in a particular data center for reasons other than, for example, they want to terminate the lease on that data center and migrate all workload elsewhere.

CEEC market maker service

CEEC market making generally refers to bringing CEEC buyers and sellers together into an environment where they will have difficulty finding each other unaided. CEEC market maker services 322 are mechanisms that bring together groups of buyer computing resources and seller computing resources and facilitate the use of existing CEECs from sellers with buyers or denial of sellers via reassociation. CEEC and replace the CEEC with a new CEEC associated with the buyer to migrate the CEEC from the seller's computing resource group to the buyer's computing resource group. In some cases, CEEC market maker services go beyond simply matching buyers and sellers for synchronous transactions, where both buyers and sellers of CEEC are known at the time of the transaction, but instead CEEC market makers can Provides capabilities for asynchronous transactions, where one side of the transaction (buyer or seller) is known and the other side (buyer or seller) is discovered using specified criteria, or where the buyer and the planned Acquisition associated with , but not existing.

Transactions for associating buyers and sellers in a CEEC market maker service not only facilitate transferring CEECs so that the terms of CEECs can be met or creating new CEECs that more closely match actual utilization under previous CEECs and associating these New CEECs are groups of computing resources and also operate to meet business goals for an organization or enterprise. That is, an organization or business may formulate rules and parameters to guide the manner in which the CEEC Market Maker Service 322 operates to achieve a specific goal. Examples of such goals may include, for example, achieving a specific energy saving goal, selling all of the CEECs associated with a given location of the organization in order to vacate the location, building a business case with a specified target dollar Utilization drives utilization of the highest value asset (computing resource), determines the cheapest place to locate a new computing resource (e.g., a piece of hardware or software), locates the place for the new computing resource that will have the greatest cost reduction Positioning, creation of prioritized CEEC migration lists based on estimated value of migration, etc.

The basic purpose of the CEEC market maker service 322 is to migrate from a source (e.g. outdated hardware/software, underutilized hardware/software, etc. (sellers)) to a sink (e.g. new hardware/software, virtualization hosts, etc. (buyers)) migrate CEECs and thus their associated workloads in order to achieve the desired goals. Groups may be designated as such in response to CEEC compliance with operational outcomes or by CEEC market maker service 322 independently identifying potential buyers and sellers based on desired goals and one or more trade specifications generated to achieve those desired goals. Buyers or sellers in the CEEC market. Transactions operated by the CEEC market maker service 322 facilitate migration. Transactions may be generated automatically, semi-automatically, or manually via the transaction builder 312 .

There are four phases of the life cycle within the CEEC market maker system 322 for a transaction, namely Creation, Call, Origination and Settlement. During the creation phase, a transaction record is created from a scratchpad or using the transaction builder 312 from a pre-existing transaction specification. The originator of the transaction (which may be a human user or an automated process) creates or selects specifications for buyers and sellers via the transaction builder 312, e.g., CEEC terms for sellers, terms for buyer computing resources or groups Configuration requirements, etc., for example, these selection specifications may include what operating system to execute on the computing resource, what type of processor, the number of processors, the amount of memory resources, the business purpose of the CEEC, the organizational unit or computing resource associated with the CEEC, or Any other identifiable parameters of CEEC. The selection may be performed by having an authorized user enter various specification parameters into a user interface element of the transaction builder 312, select those specification parameters from a list of potential specification parameters, or the like.

During the assembly phase of a transaction, a transaction originator or automated CEEC market maker service 322 uses specifications to select specific groups of seller and buyer computing resources in an organization or enterprise system. For example, a seller may be selected from the set of computing resource groups that have indicated their desire to be sellers because the results of the CEEC compliance operation indicate that CEECs need to be sold. Alternatively, sellers may be selected according to a specified business purpose by selecting groups of computing resources as sellers regardless of whether they have indicated a desire to be sellers. Alternatively, a combination of these two approaches can be used to select sellers.

Similarly, buyers may be selected from a set of groups of computing resources that have indicated their desire to be buyers. Such indication may be made in response to determining that the group of computing resources is underutilized and has capacity to accept additional CEECs. Alternatively, buyers may be selected according to a specified business purpose by selecting groups of computing resources as buyers regardless of whether they have indicated a desire to be buyers. Alternatively, a combination of these two approaches can be used to select buyers.

Where sellers and buyers are identified by available computing resource capacity in the computing resource pool and/or non-compliance with CEEC terms as determined by CEEC compliance operations, the CEEC marketplace serves as a direction with greater likelihood The manner in which the utilized computing resource group migrates the CEEC in a manner that satisfies the migrated CEEC. As mentioned above, this migration may in some cases result in disavowing the original CEEC being migrated and creating a new CEEC in association with a CEEC group that is capable of providing computing resources under the new CEEC. Compute resource group association. This new CEEC may have different utilization requirements from the original CEEC based on the contractor's measured actual utilization of the CEEC. Thus, for example, if under a first CEEC the contractor is required to use computing resources at a first level X and a weekly average usage Y of a first intensity pattern, but instead the measured utilization indicates utilization level Z and a second intensity If the mode is W average use per week, the original CEEC can be denied and a new CEEC can be created that requires the utilization of Z and the intensity mode is W average use per week. This new CEEC can be added as a member of a CEEC group associated with a computing resource group that can satisfy the terms of the new CEEC. In this scenario, the original group of computing resources associated with the original group of CEECs within the CEEC marketplace is the seller of the original CEEC and the group of computing resources associated with the new group of CEECs is the buyer of the new CEEC.

Where sellers and buyers are selected based on business goals regardless of group indications of desire to be buyers/sellers, the business goals can be identified and corresponding groups of computing resources that have characteristics that meet those business goals can be selected. This can include analyzing computing resource utilization information, configuration information, CEEC group association information, etc. to determine which computing resource groups have characteristics that meet criteria specified in the business objectives. As an example, if the business goal is to move CEECs and their associated workloads from desktop computing devices to virtual machines or servers, computing resource groups that include desktop computing devices may be identified based on configuration information associated with computing resources of the computing resource groups Group. These groups of computing resources may be selected as sellers of CEECs within the CEEC marketplace. Similarly, groups of computing resources having configuration information indicating that server computing devices have virtual server software mechanisms may be identified and selected as buyers of CEECs within the CEEC marketplace.

During the call phase, selected sellers and buyers are signaled to accept or reject the transaction. This makes selected sellers and buyers "candidate" buyers and sellers who have not yet been confirmed, as the purchase and sale can be settled at some point in the future. However, buyers and sellers may fail to meet their obligations at settlement time through no fault of their own. The convocation phase is not complete until there are enough sellers and buyers to meet the transaction's goals. So, for example, if the business objective of a deal is to migrate CEEC and its workloads from all computing resources associated with site A of the organization, the convening phase of the deal until all computing resources in the computing resource group associated with site A have been identified Groups act as sellers of CEECs and identify groups of sufficient computing resources at other sites as buyers of CEECs to enable migration of all of the CEEC groups associated with site A to these other sites.

The initiation phase of the transaction is performed in response to determining that there are sufficient buyers and sellers to satisfy the business organization of the transaction and determining that the completion of the transaction is satisfactory. Determining whether a transaction has been completed satisfactorily can be done automatically by comparing the measure of completion to one or more predetermined thresholds. For example, costs and values can be associated with various aspects of a transaction, and these costs and values can be calculated with respect to specific selected buyers and sellers to determine an actual cost/value metric for the transaction. This cost/value metric for the transaction can then be compared to one or more thresholds to determine whether the cost/value of the transaction indicates sufficient benefit to the organization/business such that the transaction should be completed.

Assuming the cost/value metric indicates that a transaction is desired to be completed, the operations needed to facilitate migration of the CEEC from the seller to the buyer are initiated. These operations may include, for example, performing various resource reservations using CEEC-based resource reservation service 328 in FIG. 3 , for example. Operations may also include, for example, operations to prepare for workload migration under CEEC, including eliminating any non-essential storage, creating OS instance containers on the buyer's system, and the like. Once these operations are performed, the buyer and seller cease to be candidates and are now officially obligated to fulfill the requirements of a buyer-seller transaction together to satisfy the transaction. Timers for any time-limited obligations under the trade can be started and monitored to ensure proper settlement of the trade.

Once a transaction is initiated, actions are initiated to execute the actual transaction between the buyer and seller until the transaction is settled, ie all transactions are successfully completed. During this process, the transaction is considered to be in the settlement phase. During this settlement phase, individual CEECs can be revoked, created and modified on an individual basis as necessary to perform the various actions required to execute the trade. For example, a CEEC may be revoked on a CEEC group associated with the seller's computing resource group, and a new CEEC may be generated and associated with the CEEC group associated with the buyer's computing resource group. As another example, a CEEC's association with a CEEC group may be modified in the CEEC to point to a different CEEC group, i.e., the CEEC group is modified such that it is overwritten with an identifier pointing to the CEEC group associated with the buyer's computing resource group. The identifier of the legacy CEEC group associated with the seller's computing resource group.

Before a transaction is conducted under a transaction specification, the cost versus value (cost/value) of the transaction can be determined and used as a basis for determining whether to actually execute the transaction and how to prioritize it over other transactions in progress. The cost/value can be determined based on the cost attributes specified in the transaction specification. That is, the transaction specification may specify cost attributes for both buyers and sellers that are of interest in determining whether the cost versus value of a transaction is such that the transaction should be performed. These costs and values need not be specified in monetary units, but can be any unit suitable for comparison between buyers and sellers. If the value of the transaction is greater than the cost by a threshold amount, where the threshold may be predetermined or specified in the transaction specification, then the transaction should be allowed to take place; otherwise the transaction should be cancelled.

Computational resources and supporting infrastructure already on the seller to perform the workload under the CEEC to be bought and sold and estimated computing resources that will be required on the buyer to perform such workload under the CEEC or replacement CEEC , an actual cost calculation is performed based on the computing resource utilization metric information for buyers and sellers. Seller cost information may be obtained from database system 330, while cost information for buyers may be based on configuration information from database system 330 and a forecasting mechanism based on configuration information for buyers and a variation of the workload associated with the CEEC. Utilization is measured to predict what the cost will be on the buyer's computing resource cluster. For example, these operations may be performed within the logic of the CEEC market maker service 322 upon determining to initiate a transaction under the transaction specifications provided by the transaction builder 312 .

A specific costing framework used to evaluate sales and purchases can take many different forms, but generally will consider fixed asset costs, infrastructure costs, hardware resource allocation costs, and software instance costs. Fixed asset cost is the cost to provide a hardware platform to a software instance regardless of how many or few software instances are hosted. That is, the test used to determine whether the cost should be encapsulated in this variable is the extent to which it must be borne regardless of the software instance. The hardware resource allocation cost is the percentage of the hardware cost that should be charged to a given software instance based on its size (and thus its use of the hardware on a percentage basis). The software instance cost is the cost of a specific software instance. In migrating from many older systems to newer, denser systems, there are readily calculable differences in the amount of floor space required, the amount of watts consumed, and the amount of cooling required. The difference is even greater when migrating to pre-existing buyers.

As mentioned above, it may be the case that the particular parties (buyers and sellers) who have been interrelated to execute the purchase and sale under the transaction are unable to meet their obligations when the transaction reaches the settlement stage, for example, in Resources that were available when the transaction was initialized are not available now. In such cases, the organization/business as a whole may maintain reserved computing resources, which may be organized into one or more groups of computing resources that may be used to allow settlement to be completed. However, these reserved computing resources need to be reacquired over time so that they can be used to assist in settling future transactions if desired. Accordingly, the CEEC market maker service 322 may generate a schedule for migrating CEECs and workloads from these reserved computing resources to groups of buyers Indicate within this period sellers who wish to act as CEECs or parts of CEECs within the CEEC marketplace. This timeline can be accelerated over time so that sell-outs occur more frequently as the time reserved computing resources have been used to contribute to the CEEC increases.

Furthermore, the reservation of the CEEC market maker service 322 can be balanced in favor of those units that buyers may find constrained, such as storage devices. In such a case, the transaction splits the storage separately to buy and sell reserved resources with margin, while the remainder of the transaction continues normally.

Thus, the reserved computing resources of the CEEC-based computing resource management system 300 allow parties in a transaction to be completed even if their counterparties fail to meet their obligations. This is another case where it is important to realize that the CEEC Market Maker Service 322 does not operate solely as a neutral party making connections, but instead is an expression of the "will of the business" and that it has Necessary means for business goals.

10A-10D are example diagrams illustrating various stages of a transaction for an example CEEC market maker-based scenario, according to an example embodiment. In the depicted example, a CEEC is generated for moving a CEEC from a secondary use desktop computer (i.e., a desktop computer that is not used for the primary computing resource of the contractor) to a virtual machine on one or more shared server computing devices, virtualization clusters, etc. Transaction Specification 1014. That is, transaction specifications 1014 are used to move CEECs and their associated workloads from physical computing devices to virtual computing devices in a virtualized environment. The transaction specification 1014 may be predefined and already stored in association with the transaction builder 1012 or may be generated from a scratchpad via a user interface provided by the transaction builder and user input 1010 received from authorized users. In the case of a predefined deal specification, the user input 1010 may be selecting a predefined deal specification from a deal specification repository associated with the deal builder 1012 , such as via a list in a user interface provided by the deal builder 1012 . Pre-existing transaction templates allow businesses to easily replicate transactions that must be done repeatedly when the number of sellers exceeds the capacity for one disposition migration.

The selection or creation of a transaction specification 1014 is performed using the transaction builder 1012 during the creation phase of the transaction. Additionally, the transaction specification 1014 is provided to the CEEC market maker service 1016, which generates one or more trade instances 1018 according to the transaction specification. The trade instance 1018 is an instance of a trade specification for performing a trade between at least one seller and at least one buyer, where the seller and the buyer are groups of computing resources. In the depicted example, trade specification 1016 is used by CEEC market maker service 1016 to create trade instances 1018 for tracking CEECs for 50 specific Used as a secondary workstation for CCCE on a virtualized cluster of 50 virtual machines (VMs). This trade instance 1018 is used by the CEEC market maker service 1016 to discover CEECs that meet the criteria of a trade instance, such as a CEEC instance corresponding to the CEEC specification 1022 for buyers, and such as a CEEC specification 1032 for sellers. CEEC instance.

It should be understood that although only a single seller CEEC specification 1022 and a single buyer CEEC specification 1032 are shown in FIGS. CEEC instances as a whole can be used to satisfy buy and sell instances 1018 and transactions. For example, in the depicted example, 50 seller CEEC instances corresponding to CEEC specification 1022 may be utilized, one instance for each of the desktop computers, and 1 buyer CEEC instance corresponding to CEEC specification 1032 may be utilized with to represent the buyer virtualization cluster of all 50 seller CEEC instances in the buyer CEEC instance.

After the transaction is created as shown in Figure 10A, the transaction proceeds to the Convocation phase as shown in Figure 10B. As shown, during the summoning phase, specific CEEC instances 1024 and 1034 associated with the seller side 1020 and buyer side 1030 of the transaction, respectively, are identified. The identification may be performed, for example, by CEEC market maker service 1016 by identifying seller-side 1020 CEEC instances 1024 that satisfy at least a portion of the seller-side requirements of transaction specification 1014 and trade instance 1018 based on transaction specification 1014 and trade instance 1018. Additionally, the identification may include identifying buyer-side 1030 CEEC instances 1034 that satisfy at least a portion of the transaction specification 1014 and buyer-side requirements of the transaction instance 1018 . These CEEC instances 1024 and 1034 are associated with specific software resources 1025 , 1035 and hardware resources 1025 , 1036 which themselves have associated infrastructure and support (eg, human support) resources 1027 , 1037 .

At this stage of the transaction, the actual seller group and buyer group are only considered to have been "solicited" and are candidate sellers and buyers only. They are not required or expected to actually participate in the transaction until the seller group and buyer group signal them to accept or reject the transaction instance 1018 . If the seller/buyer accepts the trade instance 1018, and determines that they can settle their portion of the trade instance 1018, they may become confirmed as shown in FIG. 10C. If they signal a rejection of the trade instance 1018, they are removed as candidates for satisfying the trade instance. Thus, in the call phase of a transaction, sellers and buyers are called to satisfy one or more trade instances 1018 of the transaction 1014 . A determination can be made as to whether there are sufficient sellers and buyers to meet the transaction requirements, and if not, the call phase can continue until a sufficient number of sellers and buyers are identified and receive transaction instances 1018 or if a timeout condition occurs. If a timeout condition occurs, an error condition may be returned indicating that the transaction could not be successfully completed. Appropriate authorized users may be notified of this error condition, such as via the deal builder 1012, for example, so that appropriate corrective action can be taken, eg, modification of the deal specification, manual selection of sellers and buyers, etc.

Once sufficient sellers and buyers have been called during the call-up phase of the transaction, the transaction proceeds to the initiation phase as shown in Figure 10C. During the Initiate phase, Initiate 1060 the individual work operations that are required in order to execute the trade instance 1018 . These work operations initiated (and upon completion will constitute transaction settlement) will involve, for example, configuring the virtualization infrastructure to provide 50 VMs, enabling the seller to keep the image as small as possible by uninstalling non-essential Prepare for migration, snapshot vendors and rebuild them in a virtualized cluster, grant access to appropriate users, remove all IPs from vendor hardware, unplug/remove vendor hardware, and remove vendor hardware from the base.

Once the individual job operations have been performed 1060, the settlement phase of the transaction is performed as shown in Figure 10D. During the settlement phase, a CEEC instance 1024 on the buyer side 1020 is traded or otherwise discarded to the buyer side 1030 for a new CEEC 1034 on the buyer side 1030, e.g. Replace 50 CEEC instances with a single new CEEC instance for each desktop computer, each for a single desktop computer. As a result, software resource license rights 1025 associated with traded/discarded CEEC instances 1024 on the seller's side 1020 may be migrated to the buyer's side 1030 as part of the settlement phase. These software resource license rights 1025 may be associated with OS instances, assets, or individuals and will need to be properly re-associated in the buyer group. Buyers are not expected to have 'licensed capacity', but market makers are assumed to have licenses in cases where additional licenses are required when sellers migrate (this can be the case when software is licensed to an asset as a 'preload' that cannot be delivered) fluidity. Often there is a requirement to deactivate the hardware resources 1026 on the seller side 1020 because the contractor no longer uses them to the CEEC instance 1024 and stopping their resource (power, cooling, etc.) consumption is part of the goal of the transaction. As software resources 1025 and hardware resources 1026 are migrated and retired, the need for infrastructure and support resources 1027 is circumvented and the savings achieved are tied to the transaction.

As part of the settlement phase, trade results may be generated to evaluate the outcome of the trade. These trade results may provide an indication as to the cost associated with the previous allocation of computing resources as compared to the new allocation of computing resources after the trade is completed. Such cost comparisons may be performed with respect to various costing factors including power consumption costs, cooling costs, square footage costs, depreciation costs, support costs, licensing costs, and other costs/benefits. All of these costs should be significantly lower for a virtualized cluster in the depicted example as compared to simply having 50 desktop computers with a lower number of hardware resources required to support the entitlement of 50 contractors. Such cost savings may be reported to authorized users, such as via the deal builder 1012, eg, by providing cost comparisons via a user interface or the like.

As a result of the settlement phase of the transaction, the transaction is completed and completion can be signaled to the transaction builder 1012 so that appropriate notifications can be generated and output to authorized users. The notification may include the cost comparison results as discussed above. Workloads can then be managed, routed, and executed according to the new CEEC placement, appropriate tickets can be generated for decommissioning hardware resources, support staff and infrastructure resources can be reassigned, and so on. For example, 50 virtual machine instances on a virtualization cluster are now used to perform a workload that was previously performed on 50 desktop computers, and each contractor is given a corresponding share of the 50 virtual machine instances under CEEC1034 The rights to the virtual machine instances are such that each contractor is given the same degree of rights to the virtual machine instances associated with their portion of the CEEC instance 1034 .

11A-11C depict example diagrams of a transaction specification according to an illustrative embodiment. Transaction specification 110 may be created, for example, by an authorized user via transaction builder 312 . The deal builder 312 constructs a deal specification based on input from a user specifying the goals of the business and the general characteristics of the deal type. However, once a transaction specification is created, any number of transaction instances may be automatically created by the transaction builder 312 in accordance with the transaction specification. Transaction specifications may be provided to the CEEC market maker service 322 to identify buyers and sellers, determine transaction costs, determine based on these costs whether a transaction should be executed within the CEEC market, and with other services (e.g., CEEC-based reservation service 328, database System 330, etc.) is used when executing transactions.

As shown in FIGS. 11A-11C , in the depicted example, there are five sections of the transaction. The first section 1110 of the transaction specification represents the savings target, ie what the founder of the transaction is trying to achieve in terms of savings. The second section 1120 represents the seller-side filters of the transaction, ie, the filters that should be applied to potential sellers in order to select an appropriate seller for meeting the business goals of the transaction. These seller-side filters may include schema, geographic and business unit attributes, target values indicating when a sufficient number of sellers have been selected, and the like.

The third section 1130 of the transaction specification represents seller-side cost attributes. The seller side cost attribute is an attribute representing the cost of running the workload under the current CEEC on the seller side. These are not necessarily monetary costs, but may be specified, for example, in terms of computing resource utilization or reserved quantities. As an example, a workload under the current CEEC may, for example, "spend" 5G RAM. Any cost metric can be used without departing from the spirit and scope of the illustrative embodiments so long as it facilitates cost/value comparisons between the seller and buyer sides of the CEEC marketplace. The mechanism of the exemplary embodiment has the ability to convert all costs into currency units, but this is not required for the exemplary embodiment to operate.

The fourth section 1140 of the transaction specification represents buyer side filters. These are the filters that should be applied to the set of potential buyers in order to select the appropriate buyer to meet the business objectives of the transaction. These filters may include schema, geographic and business unit attributes as well as target values indicating when enough buyers have been selected to meet the business objectives of the deal.

Section 1150 of the transaction specification represents buyer-side costs. The buyer-side cost is the cost of running the seller's workload under the existing CEEC or the new CEEC on the buyer-side computing resource cluster. Again, these are not necessarily monetary units, but may be specified in terms of computing resource usage/reservation. These costs may be converted to monetary amounts, but this is not required for the operation of the illustrative embodiment.

Transaction specifications provide context and guidance for executing transactions between buyers and sellers in the CEEC marketplace so that CEEC can be migrated from sellers to buyers for the overall purpose of the organization/enterprise. Therefore, the transaction specification also introduces market power on behalf of non-neutral CEEC market makers to enable CEEC market participation to achieve business purposes. Use CEEC as the commodity to be traded to complete the actual transaction of execution. That is, the seller is a seller of CEEC or a part of CEEC, and the buyer is a buyer of CEEC or a part of CEEC.

The CEEC market maker mechanism 322 in FIG. 3 can be used to maximize the movement of CEECs and their associated computational workload from less efficient media to more efficient media (e.g., from desktop computers to virtual servers, from legacy technology laptops moving to newer server-based services, etc.) to optimize the organization/enterprise according to the stated purpose of the organization/enterprise as specified in the transaction specification. That is, organizations may attempt to optimize their real estate usage, optimize their power usage, optimize their regulatory resource usage in a specific geography, etc.

By creating contractual instruments (ie CEECs) to allow buying and selling of these CEECs and their associated workloads, a mechanism is also provided for disbanding and summoning those same CEECs so that a given CEEC need not represent the entirety of a single system and its uses. In short, with the CEEC and CEEC market maker service 322 of the exemplary embodiment, rights and their workload need not migrate as an entire unit from system A to system B, and thus there is no need to have a relationship between the owners of system A and system B. agreement between the two to perform the migration. On the contrary, using the CEEC mechanism of the exemplary embodiment, the CEEC of system A, and thus its associated entitlement and corresponding workload, can be split into many shares on demand, and it can then be found that there can be more than the entire contract (CEEC). Easy to sell individual servings for sale. That is, where CEECs are the basis for buying and selling rather than workloads, an environment is created in which each of these buying and selling units (CEECs) can be separated and called, unbundled, bundled, and rebundled ( CEEC), all aimed at removing barriers to moving traded units (CEEC). Workloads cannot be summoned, unbundled, bundled, and rebundled without introducing the possibility of destroying workloads.

Thus, for example, with the CEEC and CEEC market maker service 322 of an exemplary embodiment, it is possible to have more than two counterparties so that buying and selling can occur between many different parties, thereby avoiding the need to find a single counter party that wants to buy exactly And everything sellers want to sell or everything sellers want to sell and buyers want to buy. For example, the counterparty (buyer or seller) can cut out only one element of the CEEC (e.g., the storage-only clause) because the buyer is the buyer of the storage contract (that is, it has available storage capacity), or the CEEC's only Regulatory support terms, since buyers have regulatory support resource capacity but no hardware capacity, etc. Thus, by being able to break up the CEEC into constituent parts, the CEEC market maker service 322 is more likely to be able to match buyers and sellers of the CEEC because of the increased pool of buyers and sellers. As a result, the business purpose specified in the transaction specification is more likely to be fulfilled via the CEEC market maker service 322 .

Additionally, it should be appreciated that "buyers" and "sellers" within the CEEC marketplace are groups of computing resources, not necessarily individual systems. Buyers are groups of computing resources that can acquire additional CEECs or portions of CEECs. Sellers are computing resource groups that can give up CEEC or part of CEEC to buyers. Thus, the substantive function of CEEC market making is not primarily to bring together a single seller with a single buyer, but this is possible with the mechanism of the exemplary embodiment, for example, a single seller of 1000 units and a single buyer of 1000 units a single buyer. On the contrary, the CEEC market, for example, finds groups or groups of buyers and groups or groups of sellers who, when combined, want to sell 1000 units and buy 1000 units. The key point is that in a market where it is only possible to have transactions between pairs that are both obliged to buy/sell each other exactly the same amount, will significantly reduce the number of transactions, and applying this to system optimization, Reduces opportunities for optimizing the system. Thus, the mechanisms of the exemplary embodiments that allow for the disbandment of bought and sold units (i.e. CEECs) allow a greater number of transactions to be successfully completed via the CEEC marketplace and thus increase the chances and possibility.

Utilizing the CEEC market maker service 322 of an exemplary embodiment, multiple different Multiple different types of buying and selling in the scene become possible. For example, using the mechanisms of the illustrative embodiments, a trade type may be based on one computing resource group having a portion of the required computing resources "on hand" while another computing resource group includes computing resources acquired by the organization or enterprise from utilizing Insufficient or outdated computing resource groups buy and sell CEECs to two different computing resource groups. In such a situation, the terms of the CEEC sold can be split between the two groups of computing resources, for example, the storage capacity that will be available in the first group of computing resources The CEEC's storage capacity terms are split between the storage capacity that becomes available on the purchased hardware.

In another scenario, a CEEC for exclusive use of a computing resource may be revoked when the computing resource is underutilized in the seller's computing resource group. Retired CEECs can be bought and sold for new CEECs, thereby sharing unutilized computing resources with other parties under terms enumerated with contracts in new CEECs. In this example, the workload is not moved, rather it shares its existing capacity, and in doing so rebuilds the effective CEEC.

In yet another scenario, CEECs may be migrated from physical hardware computing resources to virtualized computing resources, (eg, from desktop computers to virtual machines (VMs)). In migrating from physical appliances to virtual appliances (eg, from desktop computers to VMs), the power and workload of the user is migrated from the mundane scale local storage paradigm to one where storage is virtualized and more expensive per gigabit. With plentiful cheap unoccupied local storage in the realm of physical devices, users tend to fill up local storage because they correctly assume that there is no additional cost to fully utilize local storage. This presents a migration challenge when moving to storage where each additional gigabit costs significantly more.

The exemplary embodiments provide a solution to this problem by allowing storage components to be split from CEECs and "time bombarded" the storage components so that the "provisioned storage" shrinks by a fixed percentage per month after migrating CEECs.

So, for example, at migration time, 200 gigabytes of storage is allocated to the VM and there is an explicit CEEC-based agreement that this allocation will be reduced by 25% per month until the allocation reaches 50G. Therefore, the user is obliged to eliminate non-essential software and data from the system (duplicated data, redundant backups, back-end software, software no longer used, etc.) in accordance with contractual obligations. Such a CEEC will be entered so that the user is known to be able to make such a reduction and understand that it will take some time to identify and eliminate 150G of non-essential data.

FIG. 12 is a flowchart outlining example operations for executing a CEEC market transaction, according to an illustrative embodiment. The operations outlined in FIG. 12 may, for example, be performed primarily using the CEEC market maker service 322 in FIG.

As shown in FIG. 12 , operations begin with receiving user input defining a transaction specification or receiving a selection of an existing transaction specification for use in executing one or more trades of a transaction (step 1210 ). An instance of the transaction specification is created based on the transaction specification (step 1220). Seller and buyer computing resource groups are selected according to criteria specified in the transaction specification (step 1230).

The selected seller and buyer both signal acceptance or rejection of the transaction (step 1240). For sellers and buyers that signal acceptance, the selected sellers and buyers are "candidate" buyers and sellers, while for sellers and buyers that signal rejection, they are removed from the selection of potential sellers and buyers. A determination is made as to whether there are enough sellers and buyers to meet the goals of the transaction (step 1250). If not, operation returns to step 1230 so that additional selections may be made until enough sellers and buyers are selected and agreed as candidates.

In response to there being enough sellers and buyers to meet the goals of the transaction, the initiation phase of the transaction is then performed (step 1260 ). A determination is made as to whether the cost/value of the transaction indicates a desire to complete the transaction (step 1270). If not, the transaction is abandoned (step 1280) and the operation terminates with an error. If so, various operations are required to execute the sale and purchase of CEECs between the buyer and seller to achieve the business purpose of the executed transaction (step 1290). A determination is made as to whether any of the transactions used to complete the transaction could not be successfully settled (step 1300). If so, reserved computing resources may be utilized to ensure successful settlement of these transactions (step 1310). Subsequently, the CEEC market maker service is signaled that the transaction is complete (step 1320) and the operation terminates.

Accordingly, utilizing the CEEC market maker service of an illustrative embodiment, a mechanism is provided for monitoring usage of computing resources relative to a computing environment entitlement contract (CEEC) in a data processing system comprising at least one computing device and a plurality of computing resources . The mechanisms are operable to establish, by at least one computing device, one or more CEEC data structures, each CEEC data structure defining the terms of a business level agreement between a contractor and a provider of the data processing system. The terms of the CEEC specify a collection of computing resources with a specified configuration to be used by the parties for a specified purpose at a specified level and pattern of intensity for a specified period of time. The mechanisms are also operable to associate, by at least one computing device, one or more CEEC data structures with a computing resource group, where a computing resource group is a collection of similarly configured computing resources.

Additionally, the mechanisms are operable to identify, by at least one computing device, a seller of one of the one or more CEEC data structures, where the seller is a computing resource that is not utilized in accordance with terms specified in the CEEC data structure. Additionally, the mechanisms are operable to identify, by at least one computing device, a buyer of one or more of the CEEC data structures, where the buyer is a computing resource capable of satisfying terms specified in the CEEC data structure.

The mechanism is also operable to determine whether to migrate the CEEC data structure from the seller to the buyer based on the terms specified in the CEEC data structure. This determination can also be based, for example, on business goals and other criteria specified in the transaction specification. In response to determining that the CEEC data structure is to be migrated from the seller to the buyer, the CEEC data structure may be migrated from the seller to the buyer. This migration may require destroying the CEEC data structure associated with the seller and creating a replacement CEEC data structure associated with the buyer, modifying the CEEC data structure so that it is no longer associated with the seller and is now associated with the buyer, e.g., updating the group association identifier, etc.

Thus, in the above mechanism, the CEEC market maker service operates to select buyers and sellers according to the terms of the migrated CEEC and the terms of the transaction specification that defines the business goals that such CEEC migration needs to meet. These mechanisms may operate in situations where buyers have expressed interest as buyers within the CEEC market, or where sellers have expressed interest as sellers within the CEEC market, or where In , buyers and sellers are selected independently of any expressed interest as buyers or sellers. Additionally, these mechanisms may operate to match a single buyer with multiple sellers, a single seller with multiple buyers, or multiple buyers with multiple sellers. To facilitate such one-to-many, many-to-one, or many-to-many transactions, CEECs can be dissolved and buyers can buy individual portions of CEECs and sellers sell portions of CEECs to different buyers.

In other implementations, the illustrative embodiments allow groups of computing resources to register with the CEEC market maker service as buyers and sellers and specify criteria by which the CEEC market maker service may select valid sellers/buyers. For example, such criteria may be used exclusively or in combination with terms specified in the transaction specification. The CEEC market maker service then operates to match one or more buyers with one or more sellers in accordance with these terms and the terms of the transaction specification specified in the registration as buyer/seller. For example, a registration notification may be sent to CEEC market maker service 322 to add a computing resource group to the CEEC marketplace as Sellers of CEECs can also specify terms for selection buyers, for example, buyers must provide sufficient resources and resource types to satisfy actual utilization measured for the contractor and be able to provide new CEECs that match these actual utilization measurements.

That is, the illustrative embodiments may provide mechanisms for monitoring usage of computing resources with respect to a computing environment entitlement contract (CEEC) in a data processing system including at least one computing device and a plurality of computing resources. These mechanisms may establish one or more CEEC data structures, each CEEC data structure defining the terms of a business level agreement between a contractor and a provider of a data processing system. The terms of the CEEC specify a collection of computing resources with a specified configuration to be used by the parties for a specified purpose at a specified level and pattern of intensity for a specified period of time. The mechanism is also operative to receive a first request from a provider system providing one or more computing resources to be a buyer of CEEC data structures, wherein the first request includes first selection criteria for selecting a seller of CEEC data structures.

Additionally, the mechanisms of the illustrative embodiments are also operable to receive a second request from a seller system that owns a CEEC data structure requesting the seller as a CEEC data structure. The second request may include second selection criteria for selecting a buyer for the CEEC data structure. The CEEC market maker service may then pair the provider system with the seller system based on the first and second selection criteria and may migrate the CEEC data structure from the seller system to the provider system. The workload can then be executed on the provider system according to the terms specified in the CEEC data structure. It should be appreciated that this migration may involve repealing and replacing the original CEEC data structure with a new CEEC data structure with similar or different terms. In addition, CEEC data structures can represent only a part of CEEC without migrating the entire CEEC.

Thus, utilizing the mechanisms of the illustrative embodiments, facilities are provided for managing a contractor's rights to computing resources by encapsulating those rights in a contractual mechanism (ie, CEEC) that stipulates that the contractor has a right to specify The desired level and pattern of utilization for business purposes where violations result in revocation and potentially replacement of CEECs with new CEECs on the same or different computing resources. The new CEEC can be customized to correspond to the user's measured actual utilization rather than the level and pattern of utilization required by the original CEEC.

Exemplary embodiments also provide mechanisms for using the CEEC marketplace to migrate such CEECs to introduce market forces that represent an organization's or enterprise's business goals. This migration results in migrating the workload associated with the migrated CEEC, since the routing workload and contractors are now associated with the group of computing resources associated with the new or migrated CEEC. However, it should also be kept in mind that the mechanisms of the illustrative embodiments differ significantly from known workload migration mechanisms.

For example, workload migration mechanisms are known to be one-to-one migration mechanisms, meaning that one system migrates the entire workload to one other system. Migrating CEECs using the mechanisms of the illustrative embodiments allows splitting of CEECs into constituent parts such that each part can be migrated to a different target computing resource or group of computing resources. In addition, workload migration mechanisms are agnostic and non-judgmental about business purpose and usage, ie they do not determine whether computing resources are used for a specified business purpose, only whether migration of workload will increase efficiency. Workload migration does not place an obligation on migrating computing resources to specifically do anything with the old system, whereas in many cases, utilizing the mechanisms of the exemplary embodiments, CEEC includes specific obligations for decommissioning the older system, which Repeal CEEC if not done, thus invoking the user's right to use the system in its new home.

The mechanisms of the exemplary embodiments also differ from other types of workload-based arrangements, such as service level agreements, quality of service agreements, etc., as previously discussed. With such an agreement, the provider does not care how the service is used or how much of it is used, as long as the contracting parties pay them for the level or quality of service that the provider is obliged to provide. Utilizing the CEEC-based mechanisms of the exemplary embodiments, the CEEC ensures that contractors utilize associated computing resources according to specified business purposes and according to utilization levels and patterns specified in the CEEC, and otherwise performs revocation and/or migration of the CEEC.

In addition, the user in the SLA or QoS agreement does not care how the service is provided, ie what specific type of computing resources are used to provide the service quality or service level. However, utilizing the CEEC-based mechanisms of the exemplary embodiments, the CEEC can specify requirements regarding the types of computing resources to be provided under CEEC, and the CEEC market maker enforces such terms on behalf of the enterprise to ensure that computing is provided in the most efficient manner possible. resource.

As noted above, it should be appreciated that the illustrative embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements. In an example embodiment, the mechanisms of the example embodiments are implemented in software or program code including, but not limited to, firmware, resident software, microcode, and the like.

A data processing system suitable for storing and/or executing program code will include at least one processor coupled directly or indirectly to memory elements through a system bus. The memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories which provide temporary storage of at least some program code in order to reduce the number of times code must be retrieved from bulk storage during execution.

Input/output or I/O devices (including but not limited to keyboards, displays, pointing devices, etc.) can be coupled to the system either directly or through intervening I/O controllers. Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Modems, cable modem and Ethernet cards are just a few of the currently available types of network adapters.

The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and changes will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the invention, the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims (79)

1. For use together with comprising the data handling system of at least one computing equipment and a plurality of computational resources for retaining a method for the computational resource of described data handling system, described method comprises:

   By described at least one computing equipment, generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of the computational resource of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

   Set and CEEC data structure by associated one or more computational resource of described at least one computing equipment; And

   By described at least one computing equipment according to the set of one or more computational resource described in the described CEEC data structure managing of association, wherein in response to described couterparty fail approx during the time period of the described appointment of associated with described CEEC data structure appointment approx the level of described appointment and intensity mode by the set of described one or more computational resource the object for described appointment, the logic of described at least one computing equipment is abolished described CEEC data structure.
2. 2. method according to claim 1, wherein set and the CEEC data structure of associated described one or more computational resource comprise:

   The configuration information of each computational resource based on for computational resource is determined the first set of one or more computational resource group of described computational resource, is wherein similar type to the computational resource of computational resource group associations and mutually has similar configuration;

   The attribute of one or more CEEC data structure based on being safeguarded by described data handling system is determined the second set of one or more CEEC group of CEEC data structure; And

   Based on being associated with the clause of the CEEC data structure of the CEEC group of the selection of described the second set associative with the characteristic of the computational resource group of the selection of described the first set associative, mate the CEEC group of described selection and the computational resource group of described selection.
3. 3. method according to claim 2, indivedual clauses and the more than one CEEC group associations of wherein said CEEC data structure based on described CEEC data structure.
4. 4. according to claim 2 or method claimed in claim 3, wherein according to the set of one or more computational resource described in the described CEEC data structure managing of association, comprise the computational resource route workload to the set associative with described one or more computational resource according to the clause of the described CEEC data structure associated ground appointment with associated.
5. 5. method according to claim 4, wherein route workload comprises:

   From couterparty, receive workload;

   Fetch one or more CEEC data structure associated with described couterparty;

   Determine the type of described workload;

   Determine the business purpose type associated with described one or more CEEC data structure of fetching; And

   Based on described workload type and the described business purpose type determined to workload described in the computational resource route of appointment at least one the CEEC data structure in described one or more CEEC data structure of fetching.
6. 6. method according to claim 5, wherein based on described workload type and the described business purpose type determined, to workload described in the computational resource route of appointment at least one the CEEC data structure in described one or more CEEC data structure of fetching, comprise the computational resource of finding with computational resource group associations, described computational resource group is associated with the CEEC data structure having with the business purpose type of the type matching of described workload.
7. 7. according to the method described in arbitrary aforementioned claim, wherein according to the set of one or more computational resource described in the described CEEC data structure managing of association, comprise:

   From described one or more computational resource, collect utilization of resources tolerance information;

   Level and the intensity mode of the described appointment of the utilization of more described utilization of resources tolerance information and described CEEC data structure associated ground appointment with associated;

   Whether the described utilization of resources tolerance information of determine collecting is significantly different from level and the intensity mode with the described appointment of the utilization of associated described CEEC data structure associated ground appointment; And

   The level and the intensity mode that in response to the described utilization of resources tolerance information of collecting, are significantly different from described appointment, revise with at least one member relation of the member relation of the described CEEC data structure of CEEC group associations or revise set associated of described CEEC data structure and described one or more computational resource.
8. 8. method according to claim 7, wherein revises at least one member relation of member relation of described CEEC data structure or set associated of revising described CEEC data structure and described one or more computational resource and comprises by moving the level of appointment of its utilization and the member relation that the described CEEC data structure of the described utilization of resources tolerance information that intensity mode is significantly different from collection is revised described CEEC data structure to different CEEC group.
9. 9. method according to claim 7, at least one member relation and set associated of revising described CEEC data structure and described one or more computational resource of wherein revising the member relation of described CEEC data structure comprises by the set associative from described one or more computational resource and moves to the different sets with one or more computational resource is associated set associated that described CEEC data structure is revised described CEEC data structure and described one or more computational resource.
10. 10. method according to claim 9, wherein moves described CEEC to different CEEC group and comprises the level of the appointment of abolishing its utilization and the described CEEC of the described utilization of resources tolerance information that intensity mode is significantly different from collection and use from the new CEEC of described different CEEC group associations and change the described CEEC abolishing.
11. 11. according to claim 9 or method claimed in claim 10, wherein from the set associative with described one or more computational resource, to the described CEEC of the associated migration of the different sets with one or more computational resource, comprises the different sets of abolishing described CEEC, creating new CEEC and associated described new CEEC and described one or more computational resource.
12. 12. according to the method described in arbitrary aforementioned claim, and wherein said CEEC data structure comprises:

    CEEC identifier field, the sign of specifying described CEEC;

    Couterparty identifier field, storage is for the couterparty of CEEC data structure associated or the couterparty identifier of couterparty group described in unique identification;

    One or more computational resource identifier field, described computational resource, computational resource group or other computational resource groups of CEEC data structure associated described in unique identification;

    One or more business purpose field, the business purpose of one or more appointment that the described computational resource that sign identifies associatedly with described one or more computational resource identifier field can be used for according to described CEEC;

    One or more computational resource configuration field, specifies for meeting the computational resource configuration requirement of the described clause of described CEEC; And

    One or more utilizes field, for requiring section preset time of described couterparty utilization described computational resource of appointment in one or more computational resource identifier field to specify level and the intensity mode of given utilization.
13. 13. 1 kinds for retaining the device of the computational resource of data handling system, and described device comprises:

    At least one processor; And

    At least one storer, is coupled to described at least one processor, and wherein said at least one storer comprises instruction, described instruction when being carried out by described at least one processor, make described at least one processor in order to:

    Generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of the computational resource of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    Set and the CEEC data structure of associated one or more computational resource; And

    According to the set of one or more computational resource described in the described CEEC data structure managing of association, wherein in response to described couterparty fail approx during the time period of the described appointment of associated with described CEEC data structure appointment approx the level of described appointment and intensity mode by the set of described one or more computational resource the object for described appointment, described processor can be used to abolishes described CEEC data structure.
14. 14. 1 kinds for use together with comprising the data handling system of at least one computing equipment and a plurality of computational resources for monitor the method for the use of described computational resource with respect to computing environment right contract, described method comprises:

    By described at least one computing equipment, generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC data structure specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    By described at least one computing equipment, generate the CEEC group collecting that comprises the CEEC data structure with similar clause;

    By described at least one computing equipment, monitor according to the described similar clause collecting of described CEEC data structure to the utilization collecting of computational resource the use pattern with described CEEC group associations with sign; And

    The member relation of the described use schema modification by described at least one computing equipment based on sign and the CEEC data structure of described CEEC group associations.
15. 15. methods according to claim 14, wherein generate and comprise that the CEEC group collecting of the CEEC data structure with similar clause comprises:

    Definition profile, described profile is specified and is used for defining that the parameter of CEEC group and appointment can be used as the member of described CEEC group and the characteristic of the CEEC data structure that is included;

    The data that described profile is applied in the CEEC data structure in described one or more CEEC data structure meet the requirement by the described parameter appointment of described profile to determine which CEEC data structure; And

    Select one or more CEEC data structure to be contained in the collecting of described CEEC data structure of described CEEC group.
16. 16. methods according to claim 15, wherein said profile is specified at least one in the following: assess which computational resource associated with CEEC data structure and utilize metric to determine the member relation with the described CEEC data structure of described CEEC group associations; And for the member relation of the CEEC data structure with described CEEC group associations, need and described computational resource utilization tolerance information association utilize patterns.
17. 17. according to the method described in claim 15 or claim 16, and wherein said profile is specified each CEEC data structure for the member as described CEEC group and the described similar clause that must have.
18. 18. according to claim 15 to the method described in the arbitrary claim in 17, also comprises:

    Selection based on described one or more CEEC data structure is upgraded with the entry of CEEC database association to comprise the identifier of described CEEC group in entry corresponding to described one or more CEEC data structure with selecting of described CEEC database.
19. 19. according to claim 16 to the method described in the arbitrary claim in 18, wherein said profile comprises that whether for assessment of described computational resource, utilize metric take to determine CEEC data structure is the first standard of the member of described CEEC group, and wherein said the first standard comprise carry out the time limit of described assessment, for measuring the basis of described computational resource utilization and for carrying out the biasing of described assessment.
20. 20. methods according to claim 19, wherein said profile also comprise for determine when adjust with the second standard of the member relation of the CEEC data structure of described CEEC group associations and with the respective action of described the second standard association.
21. 21. methods according to claim 20, wherein said the second standard and respective action specify cause the computational resource of carrying out respective action utilize the scope of metric, wherein said respective action comprise for CEEC fairground, obtain with the additional CEEC data structure of described CEEC group associations buy in action, for using described CEEC fairground to remove selling action, moving and for making the permanent delisting delisting action of CEEC data structure for the maintenance without operation of CEEC data structure from described CEEC group.
22. 22. methods according to claim 21, wherein based on the described of sign, by pattern, revise with the described member relation of the described CEEC data structure of described CEEC group associations and comprise:

    By described the second standard application in sign described use pattern with sign respective action; And

    Described CEEC data structure is carried out to described respective action to revise thus the described member relation of described CEEC group.
23. 23. methods according to claim 22, the described respective action of wherein described CEEC data structure being carried out is to described different CEEC group, to move described CEEC data structure according to another profile from different CEEC group associations.
24. 24. methods according to claim 23, wherein move the described CEEC data structure that described CEEC data structure comprises that abolishment is abolished with replacing from the described CEEC data structure of described CEEC group associations and the new CEEC data structure of establishment and described different CEEC group associations.
25. 25. methods according to claim 24, wherein said new CEEC data structure comprises the clause different from the described CEEC data structure of abolishing, and the described clause of wherein said new CEEC data structure is similar to the described use pattern of sign.
26. 26. 1 kinds of devices for the use with respect to computing environment right contract supervision computational resource, described device comprises:

    At least one processor; And

    At least one storer, is coupled to described at least one processor, and wherein said at least one storer comprises instruction, described instruction when being carried out by described at least one processor, make described at least one processor in order to:

    Generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC data structure specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    Generation comprises the CEEC group collecting of the CEEC data structure with similar clause;

    Supervision according to the described similar clause collecting of described CEEC data structure to the utilization collecting of computational resource with sign and the use pattern of described CEEC group associations; And

    The member relation of the described use schema modification based on sign and the CEEC data structure of described CEEC group associations.
27. 27. 1 kinds of methods for the use with respect to computational resource described in the contract administration of computing environment right for using together with comprising the data handling system of at least one computing equipment and a plurality of computational resources, described method comprises:

    By described at least one computing equipment, generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    By described at least one computing equipment, generate the CEEC group collecting that comprises the CEEC data structure with similar clause;

    By described at least one computing equipment, collecting the utilization of resources of measuring the usage quantity of each computational resource associated with collecting of computational resource according to the described similar clause of described CCE group measures;

    By described at least one computing equipment, based on the described utilization of resources tolerance of collecting, calculated the relative measurement of the utilization of resources under each the CEEC data structure with described CEEC group associations; And

    Report by described at least one computing equipment output with the described relative measurement of the described utilization of resources of each CEEC data structure of CEEC group associations.
28. 28. methods according to claim 27, the relative measurement that wherein the described utilization of resources tolerance based on collecting is calculated the utilization of resources under each the CEEC data structure with described CEEC group associations also comprise business objective based on described CCE group associations for collecting of computational resource associated described computational resource in various computational resources determine the relative weighting that the utilization of resources is measured.
29. 29. methods according to claim 28, wherein the relative weighting of dynamically determining described utilization of resources tolerance is analyzed in the described resource utilization quantitative statistics based on collecting.
30. 30. according to the method described in the arbitrary claim in claim 27 to 29, and the described relative measurement that wherein the described utilization of resources tolerance based on collecting is calculated the utilization of resources under each the CEEC data structure with described CEEC group associations comprises:

    Fetch the profile corresponding with described CEEC group, wherein said profile is specified and will be used which computational resource utilization tolerance as being used to the basis of relative measurement of each the CEEC data structure computational resource utilization in described CEEC data structure and the standard of thinking the described relative measurement of each the CEEC data structure computational resource utilization in described CEEC data structure for assessment of described computational resource utilization tolerance; And

    The described relative measurement that the described computational resource utilization tolerance of the appointment based on associated with described profile and evaluation criteria computational resource utilize.
31. 31. according to the method described in the arbitrary claim in claim 27 to 30, wherein the described relative measurement of the utilization of resources comprises mark, and wherein the report of output and the described relative measurement of the described utilization of resources of each CEEC data structure of described CEEC group associations comprises the described mark of each CEEC data structure is categorized into the utilization of resources mark classification from a plurality of utilization of resources mark classifications, and described a plurality of utilization of resources mark classifications are indicated the relative utilization of described computational resource under the clause of described corresponding CEEC data structure.
32. 32. according to the method described in the arbitrary claim in claim 27 to 31, wherein the described relative measurement of the utilization of resources comprises the mark of each CEEC data structure of described indivedual CEEC data structures of part based on for as described CEEC group, mark for described CEEC group as a whole, and wherein the report of output and the described relative measurement of the described utilization of resources of each CEEC data structure of described CEEC group associations comprises the utilization of resources classification for described CEEC group as a whole from a plurality of utilization of resources mark classifications output, described a plurality of utilization of resources mark classification is indicated the relative utilization of described computational resource under the clause with similar and CEEC data structure described CEEC group associations each other.
33. 33. methods according to claim 32, also comprise:

    The profile that renewal is used for generating described CEEC group is to comprise for the described mark of described CEEC group with at least one of the described utilization of resources classification of described CEEC group.
34. 34. according to the method described in the arbitrary claim in claim 31 to 33, wherein said utilization of resources mark classification comprise the utilization of index gauge operator resource whether the computational resource in the tolerance accepted of the clause of corresponding CEEC data structure utilize the scope of mark.
35. 35. according to the method described in the arbitrary claim in claim 31 to 34, and wherein said utilization of resources classification has separately by the respective action in response to the mark associated with corresponding CEEC data structure being classified described CEEC data structure is carried out in described specific resources being utilized classification.
36. 36. methods according to claim 35, wherein said respective action comprises at least one in the following: deny described CEEC data structure, by new CEEC data structure, change described CEEC data structure and to another CEEC group, move described CEEC data structure from described CEEC group.
37. 37. according to the method described in the arbitrary claim in claim 31 to 36, also comprises:

    Based on being associated with the member relation of revising described at least one CEEC data structure with the classification of the mark of at least one CEEC data structure of CEEC group associations; And

    Based on described CEEC group, carry out with the associated workload of controlling of the set of one or more computational resource with described CEEC group.
38. 38. according to the method described in the arbitrary claim in claim 31 to 37, and wherein described utilization of resources mark classification is determined in the selection of at least one in the demonstration CEEC data structure based in described CEEC group and anti-demonstration CEEC data structure.
39. 39. 1 kinds of devices for the use with respect to computing environment right contract administration computational resource, described device comprises:

    At least one processor; And

    At least one storer, can be coupled to described at least one processor, and wherein said at least one storer comprises instruction, described instruction when being carried out by described at least one processor, make described at least one processor in order to:

    Generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    Generation comprises the CEEC group collecting of the CEEC data structure with similar clause;

    The utilization of resources that collection is measured the usage quantity of each computational resource associated with collecting of computational resource according to the described similar clause of described CEEC group is measured;

    Based on the described utilization of resources tolerance of collecting, calculate the relative measurement of the utilization of resources under each the CEEC data structure with described CEEC group associations; And

    The report of the described relative measurement of the described utilization of resources of each CEEC data structure of output and CEEC group associations.
40. 40. 1 kinds for use together with comprising the data handling system of at least one computing equipment and a plurality of computational resources for the method from a computational resource to another computational resource migration computing environment right contract, described method comprises:

    By described at least one computing equipment, generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    By one or more CEEC data structure and computational resource group described in described at least one computing equipment association, wherein said computational resource group comprises the collecting of computational resource with similar configuration;

    By described at least one computing equipment sign and described one or more CEEC data structure seller associated, CEEC data structure;

    By described at least one computing equipment sign and described one or more CEEC data structure buyer associated, CEEC data structure;

    From described seller to described buyer, move described CEEC data structure; And

    After moving described CEEC data structure from described seller to described buyer described buyer according to the clause execution work amount of associated with described CEEC data structure appointment, wherein said seller and described buyer comprise collecting of computational resource or computational resource.
41. 41. according to the method described in claim 40, wherein said seller comprises not according to the computational resource that the described clause of appointment is utilized associatedly with described CEEC data structure, and wherein said buyer comprises and can meet the computational resource of the described clause of appointment associatedly with described CEEC data structure.
42. 42. according to the method described in claim 40 or claim 41, and wherein the described clause based on associated with described CEEC data structure appointment is carried out and determined whether to move from described seller to described buyer described CEEC data structure.
43. 43. according to the method described in the arbitrary claim in claim 40 to 42, also comprise whether the business objective standard based on associated with transaction standard moves described CEEC data structure from described seller to described buyer, wherein only in response to the described migration of determining described CEEC data structure, meet the described business objective standard associated with described transaction standard and carry out the described described CEEC data structure of moving from described seller to described buyer.
44. 44. according to the method described in claim 43, and wherein said transaction standard builds device user interface by user with transaction and generates, and wherein said user specifies described business objective standard by described transaction structure device user interface.
45. 45. according to the method described in claim 43 or claim 44, wherein based on described transaction standard, generate for move a plurality of transaction examples of CEEC data structure between seller and buyer, and the described business objective standard of wherein said transaction standard and each transaction example make together for determine whether by carry out and the associated seller of described transaction example and buyer between move CEEC data structure.
46. 46. according to the method described in the arbitrary claim in claim 43 to 45, and the seller who wherein carries out sign CEEC data structure according to the described business objective standard of the example of described transaction standard is, identify the buyer of CEEC data structure and move described CEEC data structure from described seller to described buyer.
47. 47. according to the method described in claim 46, and at least one in wherein said seller or buyer do not indicated and wished as seller or buyer before identifying described seller and buyer according to the described business objective standard of the described example of described transaction standard.
48. 48. according to the method described in claim 46 or claim 47, wherein according to the described example of described transaction standard, carry out and from described seller to described buyer, move described CEEC data structure, and wherein by four transactional stage, carry out the described example of described transaction standard, described four transactional stage comprise the establishing stage of the described example that wherein creates described transaction standard, wherein said seller and described buyer's signal notice are accepted convening the stage of described transaction, wherein about completing described migration, whether meet the accounts settling phase that the described business objective standard associated with the described example of described transaction standard carried out definite mounting phase and wherein complete described migration between described seller and described buyer.
49. 49. according to the method described in the arbitrary claim in claim 40 to 48, wherein from described seller to described buyer, moves described CEEC data structure and comprises the described CEEC data structure the described seller of abolishment and create the new CEEC data structure on described buyer.
50. 50. according to the method described in the arbitrary claim in claim 40 to 49, wherein from described seller to described buyer, moves described CEEC data structure and comprises that the identifier associated with described CEEC data structure of resetting is to identify described buyer.
51. 51. according to the method described in the arbitrary claim in claim 40 to 50, the subdivision of the CEEC of wherein said CEEC data structure representative between described couterparty and described supplier, wherein said subdivision define described CEEC described clause can be by the satisfied subdivision of the computational resource being provided by described supplier, and other computational resources that other subdivisions of the described clause of wherein said CEEC are provided by other suppliers meet.
52. 52. 1 kinds of devices for the migration computing environment right contract from a computational resource to another computational resource, described device comprises:

    At least one processor; And

    At least one storer, can be coupled to described at least one processor, and wherein said at least one storer comprises instruction, described instruction when being carried out by described at least one processor, make described at least one processor in order to:

    Generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    Associated described one or more CEEC data structure and computational resource group, wherein said computational resource group comprises the collecting of computational resource with similar configuration;

    Sign and described one or more CEEC data structure seller associated, CEEC data structure;

    Sign and described one or more CEEC data structure buyer associated, CEEC data structure;

    From described seller to described buyer, move described CEEC data structure; And

    After moving described CEEC data structure from described seller to described buyer described buyer according to the clause execution work amount of associated with described CEEC data structure appointment, wherein said seller and described buyer comprise collecting of computational resource or computational resource.
53. 53. 1 kinds for use together with comprising the data handling system of at least one computing equipment and a plurality of computational resources for the method from a computational resource to another computational resource migration computing environment right contract, described method comprises:

    By described at least one computing equipment, generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    By described at least one computing equipment, from providing supplier's system of one or more computational resource to receive request as the first request of the buyer of CEEC data structure, wherein said the first request comprises for selecting the first choice criteria of the seller of described CEEC data structure;

    By described at least one computing equipment, from having seller's system of CEEC data structure, receive request as the second request of the seller of described CEEC data structure, wherein said the second request comprises the second choice criteria that is used to described CEEC data structure to select buyer;

    By described at least one computing equipment, based on described the first choice criteria and described the second choice criteria, described supplier's system and described seller's system are matched;

    From described seller's system to CEEC data structure described in described supplier's system migration; And

    According to the associated described clause execution work amount in described supplier's system of the described CEEC data structure with migration.
54. 54. according to the method described in claim 53, wherein said the first choice criteria specify described buyer to provide certain quantity computational resource requirement and for meeting at least one item of certain computational resource type that the computational resource of the measurement corresponding with described CEEC data structure utilizes.
55. 55. according to the method described in claim 53 or claim 54, and wherein said the second choice criteria specifies described seller to utilizing at least one in the requirement of computational resource of certain quantity and certain computational resource type.
56. 56. according to the method described in the arbitrary claim in claim 53 to 55, also comprise based on the associated business objective standard of transaction standard whether from described seller's system to CEEC data structure described in described buyer's system migration, wherein only in response to the described migration of determining described CEEC data structure meet the described business objective standard associated with described transaction standard carry out described in from described seller's system to CEEC data structure described in described buyer's system migration.
57. 57. according to the method described in claim 56, and wherein said transaction standard builds device user interface by user with transaction and generates, and described user specifies described business objective standard by described transaction structure device user interface.
58. 58. according to the method described in claim 56 or claim 57, wherein based on described transaction standard, generate for move a plurality of transaction examples of CEEC data structure between seller's system and buyer's system, and the described business objective standard of wherein said transaction standard and each transaction example make together for determine whether by execution and the associated seller's system of described transaction example and buyer's system between move CEEC data structure.
59. 59. according to the method described in the arbitrary claim in claim 56 to 58, wherein according to the described business objective standard of the example of described the first choice criteria, described the second choice criteria and described transaction standard, carries out described seller's system and the pairing of described buyer's system.
60. 60. according to the method described in claim 59, at least one buyer's system in wherein said buyer's system is one of a plurality of buyer's systems, by the described clause based on associated with described CEEC data structure, described CEEC data structure is separated into component part, described a plurality of buyer's systems are bought in a part for described CEEC data structure separately.
61. 61. according to the method described in claim 59 or claim 60, wherein according to the described example of described transaction standard, carry out and from described seller to described buyer, move described CEEC data structure, and wherein by four transactional stage, carry out the described example of described transaction standard, described four transactional stage comprise the establishing stage of the described example that wherein creates described transaction standard, wherein said seller's system and described buyer's system signal notice are accepted convening the stage of described transaction, wherein about completing described migration, whether meet the accounts settling phase that the described business objective standard associated with the described example of described transaction standard carried out definite mounting phase and wherein complete described migration between described seller's system and described buyer's system.
62. 62. according to the method described in the arbitrary claim in claim 53 to 61, wherein from described seller to described buyer, moves described CEEC data structure and comprises the described CEEC data structure the described seller's system of abolishment and create the new CEEC data structure in described buyer's system.
63. 63. according to the method described in the arbitrary claim in claim 53 to 62, wherein from described seller's system to CEEC data structure described in described buyer's system migration, comprises that the identifier associated with described CEEC data structure of resetting is to identify described buyer's system.
64. 64. according to the method described in the arbitrary claim in claim 53 to 63, and wherein said buyer's system and described seller's system comprise computational resource group separately, and described computational resource group comprises a plurality of computational resources.
65. 65. 1 kinds of devices for the migration computing environment right contract from a computational resource to another computational resource, described device comprises:

    At least one processor; And

    At least one storer, can be coupled to described at least one processor, and wherein said at least one storer comprises instruction, described instruction when being carried out by described at least one processor, make described at least one processor in order to:

    Generate one or more computing environment right contract (CEEC) data structure, each CEEC data structure definition is at the clause of the couterparty of described data handling system and the agreement of the professional skill between supplier, the set of the computational resource of the configuration that the described clause of wherein said CEEC specifies object that the time period for appointment is used to specify by described couterparty at level and the intensity mode of appointment, have appointment;

    From providing supplier's system of one or more computational resource to receive request as the first request of the buyer of CEEC data structure, wherein said the first request comprises for selecting the first choice criteria of the seller of described CEEC data structure;

    From having seller's system of CEEC data structure, receive request as the second request of the seller of described CEEC data structure, wherein said the second request comprises the second choice criteria that is used to described CEEC data structure to select buyer;

    Based on described the first choice criteria and described the second choice criteria, described supplier's system and described seller's system are matched;

    From described seller's system to CEEC data structure described in described supplier's system migration; And

    According to the associated described clause execution work amount in described supplier's system of the described CEEC data structure with migration.
66. 66. 1 kinds for use together with comprising the data handling system of at least one computing equipment and a plurality of computational resources for managing the method for the use of described computational resource, described method comprises:

    By computing environment right contract (CEEC) manager, generate one or more CEEC, wherein each CEEC comprises a plurality of clauses, and wherein the described clause of CEEC specify object that the time period for appointment is used to specify by couterparty at level and the intensity mode of appointment, the set of the computational resource of the configuration with appointment;

    By group and profile manager, generate one or more group's profile, the common features of each group's profile designated group wherein, each member of group comprise described common features in case with described group associations;

    One or more profile define and represent by management and group service based on being generated by described group and profile manager is from the computational resource group of the computational resource group of described a plurality of computational resources, and the CEEC group of one or more profile define and represent CEEC group based on being generated by described group and profile manager; And

    Described computational resource group by Database Systems based on definition and the storage of CEEC group and described a plurality of computational resources, described one or more CEEC and the computational resource associated corresponding data with CEEC.
67. 67. according to the method described in claim 66, also comprises:

    By the computational resource that utilizes marking service for the described computational resource collection of each CEEC with described CEEC group associations based on to from described computational resource group associations, utilize the analysis of metric to carry out generating fractional value.
68. 68. according to the method described in claim 67, the member relation of the described fractional value management of wherein said management and group service based on by described utilization marking service creation and the computational resource of described computational resource group associations and with the member relation of the CEEC of described CEEC group associations.
69. 69. according to the method described in the arbitrary claim in claim 66 to 68, also comprises:

    By the transaction associated with CEEC fairground of CEEC market manipulation person service execution to exchange CEEC between buyer's computational resource and seller's computational resource.
70. 70. according to the method described in claim 69, wherein said buyer's computational resource comprises buyer's computational resource group, described buyer's computational resource group has available computational resources to meet one or more clause of the CEEC being sold by described seller's computational resource, and wherein said seller's computational resource comprises seller's computational resource group, for described seller's computational resource group, computational resource utilizes metric to refer to not meet the clause of the described CEEC being sold by the utilization of the described computational resource with described seller's computational resource group associations.
71. 71. according to the method described in the arbitrary claim in claim 66 to 70, also comprises:

    By user, by the user interface that transaction builds device, carry out given transaction profile, wherein said transaction profile is specified for carrying out buyer's computational resource of example and the characteristic of seller's computational resource of described transaction profile.
72. 72. according to the method described in claim 71, and wherein said CEEC market manipulation person service is selected described buyer's computational resource and seller's computational resource according to the described characteristic of buyer's computational resource and seller's computational resource.
73. 73. according to the method described in claim 71 or claim 72, wherein user specifies the business objective standard of described transaction profile by the described user interface of described transaction structure device, and wherein said business objective standard is specified for having ratified the standard of the example of the described transaction profile of execution.
74. 74. according to the method described in the arbitrary claim in claim 71 to 73, wherein said CEEC market manipulation person service is based on the described business objective standard cost associated with the example of described transaction standard, and the described example associated described cost of wherein said CEEC market manipulation person service based on described transaction determines whether to have allowed the described example of described transaction standard.
75. 75. according to the method described in the arbitrary claim in claim 66 to 74, also comprises:

    By one or more associated information technology management warehouse system of one or more website with tissue, from a plurality of computational resources of the website of described one or more information technology management warehouse system associated, collect computational resource and utilize metric, described one or more website of wherein said tissue comprises described a plurality of computational resource separately.
76. 76. according to the method described in the arbitrary claim in claim 66 to 75, also comprises:

    Associated to computational resource route workload by work load management service based on described CEEC group and described computational resource group.
77. 77. according to the method described in the arbitrary claim in claim 66 to 76, also comprises:

    By interface, dock described Database Systems and the existing computing system of organizing, the described existing computing system of organizing provides the information about the institutional framework of described tissue, and wherein with described interface, upgrades the entry associated with the described Database Systems of the described computational resource of described CEEC corresponding to described CEEC group and described computational resource group to comprise from the described existing information of organizing the described institutional framework about described tissue that computing system obtains.
78. 78. 1 kinds of devices for the use of Management Calculation resource, described device comprises:

    Computing environment right contract (CEEC) manager, can be used to and generate one or more CEEC, wherein each CEEC comprises a plurality of clauses, and wherein the described clause of CEEC specify object that the time period for appointment is used to specify by couterparty at level and the intensity mode of appointment, the set of the computational resource of the configuration with appointment;

    Group and profile manager, can be used to and generate one or more group's profile, the common features of each group's profile designated group wherein, each member of group comprise described common features in case with described group associations;

    Management and group service, can be used to one or more profile define and represent based on being generated by described group and profile manager from the computational resource group of the computational resource group of described a plurality of computational resources, and the CEEC group of one or more profile define and represent CEEC group based on being generated by described group and profile manager; And

    Database Systems, for the described computational resource group based on definition and the storage of CEEC group and described a plurality of computational resources, described one or more CEEC and the computational resource associated corresponding data with CEEC.
79. 79. 1 kinds of computer programs, comprise be suitable for carrying out according to described in the arbitrary claim in claim 1-12,14-25,27-38,40-51,53-64 and 66-67 program code devices in steps.

Images