CN113448721A - Network system for computing power processing and computing power processing method - Google Patents
Network system for computing power processing and computing power processing method Download PDFInfo
- Publication number
- CN113448721A CN113448721A CN202010232182.0A CN202010232182A CN113448721A CN 113448721 A CN113448721 A CN 113448721A CN 202010232182 A CN202010232182 A CN 202010232182A CN 113448721 A CN113448721 A CN 113448721A
- Authority
- CN
- China
- Prior art keywords
- computing
- computing power
- information
- network
- service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5072—Grid computing
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/50—Indexing scheme relating to G06F9/50
- G06F2209/508—Monitor
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
- Power Sources (AREA)
Abstract
本发明实施例提供的一种算力处理的网络系统及算力处理方法，该系统包括：第一处理层、第二处理层以及第三处理层；第一处理层用于获取业务的服务请求；第二处理层用于至少根据服务请求获得算力配置策略；第三处理层用于根据算力配置策略选择对应的网络路径，将业务调度到对应的算力网元节点进行处理；本发明实施例基于无处不在的网络连接将动态分布的计算资源互联，通过网络、存储、算力等多维度资源的统一协同调度，使海量的业务能够按需、实时调用不同地方的计算资源，实现连接和算力在网络的全局优化，提供一致的用户体验。
A computing power processing network system and computing power processing method provided by an embodiment of the present invention include: a first processing layer, a second processing layer, and a third processing layer; the first processing layer is used to obtain a service request of a business The second processing layer is used to obtain the computing power configuration strategy at least according to the service request; the third processing layer is used to select the corresponding network path according to the computing power configuration strategy, and schedule the service to the corresponding computing power network element node for processing; the present invention The embodiment interconnects dynamically distributed computing resources based on ubiquitous network connections, and enables massive businesses to call computing resources in different places in real time on demand through the unified coordinated scheduling of multi-dimensional resources such as network, storage, and computing power, thereby realizing Global optimization of connections and computing power in the network to provide a consistent user experience.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a computing power processing network system and a computing power processing method, or a computing power sensing network or a computing power network.
Background
Under the development trend of cloud computing and edge computing, computing power of many different scales can be distributed at different distances close to users in future society, and various personalized services are provided for the users through a global network. From a billion-magnitude intelligent terminal, to a billion-magnitude home gateway all over the world, to thousands of edge clouds with computing capability brought by future edge computing in each city, and to dozens of large cloud data centers DC in each country, a huge amount of ubiquitous computing power is formed, and the development trend of computing and network deep fusion is formed. Computing resources in the network are integrated into each corner of the network, so that each network node can become a resource provider, and a user request can be satisfied by calling the nearest node resource and is not limited to a specific node, thereby avoiding waste of connection and network scheduling resources. However, the traditional network is only a pipeline for providing data communication, and is based on connection, and is limited by a fixed network addressing mechanism, which often cannot meet the higher and more rigorous QoE requirements. In addition, with the development of micro-services, a traditional client-server (server) mode is deconstructed, application deconstruction functional components on the server side are distributed on a cloud platform and are uniformly scheduled by an API gateway, dynamic instantiation can be achieved as required, the service in the server is logically transferred to the client side, and the client only needs to care about the computing function and does not need to care about computing resources such as the server, a virtual machine and a container, so that the service function is realized.
Therefore, a new generation network architecture facing a future network needs to cooperatively consider the requirements of network and calculation fusion evolution, so that the global optimization of the network in the ubiquitous connection and computing architecture, the flexible scheduling of computing power and the reasonable distribution of services are realized; however, conventional networks do not enable computational resource allocation.
Disclosure of Invention
The embodiment of the invention aims to provide a computing power processing network system and a computing power processing method, so as to solve the problem that a network in the prior art cannot realize computing power resource allocation.
In order to solve the above problem, an embodiment of the present invention provides a computing power processing network system, including:
a first processing layer, a second processing layer and a third processing layer;
the first processing layer is used for acquiring a service request of a service and sending the service request to the second processing layer;
the second processing layer is used for obtaining a calculation force configuration strategy at least according to the service request and sending the calculation force configuration strategy to the third processing layer;
the third processing layer is used for selecting a corresponding network path at least according to the computing power configuration strategy and dispatching the service to a corresponding computing power network element node for processing;
wherein the third process layer is further configured to:
acquiring network resource information;
and selecting a corresponding network path at least according to the computing power configuration strategy and the network resource information, and scheduling the service to a corresponding computing power network element node for processing.
Wherein the computing power processing network system further comprises: a fourth process layer;
the fourth processing layer is used for acquiring computing power resource state information of the computing power network element node and sending the computing power resource state information to the second processing layer;
and the second processing layer obtains the computing power configuration strategy at least according to the service request and the computing power resource state information.
Wherein the second handle layer is further configured to:
carrying out abstract description and representation on the computing power resource state information to generate a computing power capability template;
and generating a computing power service contract at least according to the computing power capability template and the service request.
Wherein the second handle layer is further configured to:
and sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node.
Wherein the second handle layer is further configured to:
and performing performance monitoring on the state information of the computing resources of the computing network element nodes, and sending at least one of the performance of the computing resources, the computing cost management information and the computing resource fault information to the corresponding computing network element nodes.
Wherein the computing resource status information comprises at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
Wherein the fourth processing layer sends the computing resource state information to the second processing layer, including:
and the second processing layer sends a calculation force measurement request message to the fourth processing layer and receives a calculation force state information response message fed back by the fourth processing layer, wherein the calculation force state information response message carries calculation force resource state information of calculation force network element nodes.
Wherein the fourth processing layer sends the computing resource state information to the second processing layer, including:
and the fourth processing layer reports the computing resource state information of the computing network element node to the second processing layer periodically or non-periodically.
Wherein the computation power measurement request message includes at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
And the second processing layer carries the calculation force measurement request message through the telemetry information of the operation maintenance management (OAM).
The embodiment of the invention also provides a computing power processing method, which is applied to a network system for computing power processing and comprises the following steps:
acquiring a service request of a service;
obtaining a computing power configuration strategy at least according to the service request mapping;
and selecting a corresponding network path at least according to the computing power configuration strategy, and scheduling the service to a corresponding computing power network element node for processing.
Wherein the method further comprises:
acquiring network resource information;
and selecting a corresponding network path at least according to the computing power configuration strategy and the network resource information, and scheduling the service to a corresponding computing power network element node for processing.
Wherein the method further comprises:
acquiring computing resource state information of a computing network element node;
and obtaining the computing power configuration strategy at least according to the service request and the computing power resource state information.
Wherein the method further comprises:
carrying out abstract description and representation on the computing power resource state information to generate a computing power capability template;
and generating a computing power service contract at least according to the computing power capability template and the service request.
Wherein the method further comprises:
and sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node.
Wherein the method further comprises:
and performing performance monitoring on the state information of the computing resources of the computing network element nodes, and sending at least one of the performance of the computing resources, the computing cost management information and the computing resource fault information to the corresponding computing network element nodes.
Wherein the computing resource status information comprises at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
The embodiment of the invention also provides a network system for computing power processing, which comprises a memory, a processor and a program stored on the memory and capable of running on the processor, wherein the processor realizes the computing power processing method when executing the program.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps in the computational power processing method described above.
The technical scheme of the invention at least has the following beneficial effects:
the network system for computing power processing and the computing power processing method provided by the embodiment of the invention have the advantages that dynamically distributed computing resources are interconnected based on ubiquitous network connection, and massive services can call computing resources in different places in real time as required through unified and collaborative scheduling of multidimensional resources such as network, storage and computing power, so that the global optimization of connection and computing power in a network is realized, and consistent user experience is provided.
Drawings
Fig. 1 is a schematic structural diagram of a computational processing network system according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating obtaining of state information of computing resources in a computing power processing network system according to an embodiment of the present invention;
fig. 3 is a diagram illustrating an example of OAM telemetry information in a computationally-processed network system provided by an embodiment of the present invention;
fig. 4 is a flowchart illustrating steps of a computational processing method according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, an embodiment of the present invention provides a computing power processing network system, including:
a first processing layer (also referred to as a power service layer), a second processing layer (also referred to as a power platform layer), and a third processing layer (also referred to as a power routing layer);
the first processing layer is used for acquiring a service request of a service and sending the service request to the second processing layer;
the second processing layer is used for obtaining a calculation force configuration strategy at least according to the service request and sending the calculation force configuration strategy to the third processing layer; for example, the service request includes parameters such as service ID, service type, service level, latency, etc. Mapping to a corresponding computational power configuration policy: CPU/GPU resource configuration requirements, storage configuration requirements, and the like.
And the third processing layer is used for selecting a corresponding network path at least according to the computing power configuration strategy and dispatching the service to a corresponding computing power network element node for processing.
Wherein the third process layer is further configured to:
acquiring network resource information;
and selecting a corresponding network path at least according to the computing power configuration strategy and the network resource information, and scheduling the service to a corresponding computing power network element node for processing.
It should be noted that the third processing layer may periodically or dynamically acquire the network resource information from the network resource layer in fig. 1, or the network resource layer actively reports the network resource information, so that the third processing layer can select a corresponding network path according to the computational power configuration policy and the current network resource information, and schedule the service to a corresponding computational power network element node for processing. The current network resource information may be understood as network resource information newly acquired by the third processing layer or network resource information newly reported by the network resource layer.
Optionally, the network path selected by the third processing layer is a current optimal network path, and the computational power network element node scheduled by the third processing layer is the current optimal computational power network element node, which is not specifically limited herein.
Wherein, the force calculation network element node refers to a network device with force calculation; further, a computational power routing node (a network device which is located in a computational power routing layer and is responsible for the notification and transmission of computational power resource information in the network, and may be a router device with computational power awareness capability) and a computational power node (a device with only computational power, which is equivalent to a device for processing computational tasks in the network, such as a server device of a data center) can be included.
In the embodiment of the present invention, the computational network element node is a network node disposed in a network resource layer as shown in fig. 1. The network resource layer is used for providing network infrastructure for information transmission, and comprises an access network, a metropolitan area network and a backbone network.
The network system for computing power processing provided in the above embodiments of the present invention may also be referred to as a system oriented to computing network convergence, a computing power sensing network system, a computing power network system, or the like, and is not limited specifically herein.
In order to realize perception, interconnection and cooperative scheduling of ubiquitous computing and services, a network oriented to computing network convergence is logically and functionally divided into a first processing layer, a second processing layer and a third processing layer. It should be noted that, in the embodiment of the present invention, the first processing layer, the second processing layer, and the third processing layer are divided according to logic functions, and in actual deployment, each of the processing layers may be deployed on one device or may be deployed on multiple devices; if the device is deployed on one device, information transmission can be carried out between the processing layers through the internal interface; if the device is deployed on a plurality of devices, information transmission can be realized among all processing layers through signaling interaction. Optionally, the specific names of the first processing layer, the second processing layer, and the third processing layer are not limited in the embodiment of the present invention, and all layer names capable of implementing the corresponding functions are applicable to the embodiment of the present invention. For example, the second processing layer, which may also be referred to as a computing platform layer, a computing power management device, a computing power management node, a computing power management layer, etc., is not necessarily enumerated herein.
The system for computing network convergence provided by the embodiment of the invention is based on computing resources where the network is ubiquitous, the computing platform layer finishes abstraction, modeling, control and management of the computing resources and informs the computing routing layer, and the computing routing layer comprehensively considers user requirements, network resource conditions and computing resource conditions and schedules services to appropriate computing network element nodes so as to realize optimal resource utilization and ensure extreme user experience.
In the embodiment of the present invention, the scheduling of the service to the corresponding computational element node includes at least two ways:
the first method is as follows: and (3) computing resource scheduling (namely selecting a corresponding network path according to the computing configuration strategy and scheduling the service to a corresponding computing network element node for processing), matching the service and the computing power and scheduling the service to a proper computing node for service processing. That is, computing-based scheduling enables finding the best-purpose serving compute node.
The second method comprises the following steps: computing resource scheduling + network resource scheduling (namely, selecting a corresponding network path according to the computing configuration strategy and the network resource information, and scheduling the service to a corresponding computing network element node for processing); the calculation resource scheduling is combined with the scheduling of the existing network resource information (for example, the network resource information comprises bandwidth, time delay jitter and the like) in the network; the calculation resource scheduling realizes the scheduling of the service to the proper calculation node, and the network resource scheduling can realize the searching of the optimal network path of the target service calculation node. Namely, scheduling based on network and scheduling of computing power (combining computing power resource scheduling and network resources), through the optimal network path, and performing optimal computing power service processing, thereby providing optimal user experience.
As shown in fig. 1, the computation force service layer supports application solution to form an atomization functional component and an algorithm library, and the algorithm library is uniformly scheduled by the API gateway to realize instantiation of the atomization algorithm in the ubiquitous computation force resource as required. Through the I1 interface, the computing power service layer passes service requests of the business or application to the computing power platform layer.
The computing platform layer needs to complete perception, measurement and OAM management of computing resources so as to support the perception, measurement, management and control of the computing resources by the network, which is beneficial to realizing joint scheduling of the computing network and improving the resource utilization rate of the operator network.
And the computation routing layer is used for discovering based on the abstracted computing resources, comprehensively considering the network condition and the computing resource condition and flexibly dispatching the service to different computation network element nodes according to the requirement. The specific functions mainly comprise calculation force route identification, calculation force route control, calculation force state network notification, calculation force route addressing, calculation force route forwarding and the like.
As an alternative embodiment, the network system for computing power processing further includes: a fourth processing layer (also referred to as a computational resource layer);
the fourth processing layer is used for acquiring computing power resource state information of computing power network element nodes and sending the computing power resource state information to the second processing layer;
and the second processing layer obtains the computing power configuration strategy at least according to the service request and the computing power resource state information.
The computing resource state information is used to reflect information such as a ubiquitous computing capability state and a deployment location in a network, and may refer to capabilities of a service connection number, CPU/GPU computing power, a deployment form (physical, virtual), a deployment location (corresponding IP address), a storage capacity, a storage form, and the like, or may refer to computing capabilities abstracted based on the basic computing resources, and is used to reflect currently available computing capabilities of each node of the network and a distributed location and form.
Similarly, the fourth processing layer is also divided according to logic functions, and in actual deployment, each of the first processing layer, the second processing layer, the third processing layer, and the fourth processing layer may be deployed on one device or may be deployed on multiple devices; if the device is deployed on one device, information transmission can be carried out between the processing layers through the internal interface; if the device is deployed on a plurality of devices, information transmission can be realized among all processing layers through signaling interaction.
In order to meet the diversity calculation requirements in the field of edge calculation, aiming at different applications, the Morel law is restored at a system level and calculation innovation is promoted by combining various calculation forces from a single-core CPU (central processing unit) to a multi-core CPU, to a CPU + GPU (image processor) + FPGA (field programmable gate array) and the like. In the face of various heterogeneous computing resources distributed in a network, the fourth processing layer needs to collect and report computing resource state information.
As another alternative, the second processing layer (i.e., the computing platform layer) is further configured to:
carrying out abstract description and representation on the computing power resource state information to generate a computing power capability template;
and generating a computing power service contract at least according to the computing power capability template and the service request.
In the face of heterogeneous computing resources, as shown in fig. 1, the computing force platform layer includes a "computing force modeling" submodule, which first needs to research a computing force resource measurement dimension and a measurement and weighing system, and forms a corresponding computing force capability template through information such as a requirement of a general algorithm or a custom usage. And combining the plurality of computing power capability templates and the service request of the service into a computing power service contract for meeting the computing power requirement of the service.
It should be noted that, in the above embodiments of the present invention, the term "at least according to" is understood as: in order to make the obtained result accurate, those skilled in the art can refer to other parameters related to calculation power to obtain better parameters based on the common means in the art, which are not enumerated herein.
Further, in the foregoing embodiment of the present invention, the second processing layer (i.e., the force platform layer) is further configured to:
and sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node. For example, the second processing layer first sends the computational capability template and/or the computational service contract to the third processing layer, and the computational capability template and/or the computational service contract is forwarded to the corresponding computational network element node by the third processing layer, or the computational capability template and/or the computational service contract is directly sent to the computational network element node by the second processing layer, where a specific sending path is not limited herein.
Optionally, the computing capability template is mainly used for unifying some information requesting modes between the computing capability processing network system and the user equipment, for example, after the computing capability processing network system receives a service request of a service, the service request is converted into information conforming to a system processing format according to the computing capability template, so as to facilitate subsequent processing; or after the user equipment receives the computing capability template (which can be acquired by the computing capability network element node), before sending the service request, the user equipment converts the relevant information of the service request into information conforming to the system processing format through the computing capability template, so that the subsequent processing of the system is facilitated, and the processing load of the system is reduced.
Optionally, the computing power service contract is mainly used for generating a corresponding computing power service contract according to the user subscription information, and once the user service comes in, the network needs to provide a corresponding computing power service according to the computing power service contract. In addition, after obtaining the computation force service contract, the user equipment may obtain which computation force network element node the user equipment can communicate with, and obtain a charging rule, and the like, which is not specifically limited herein.
As shown in fig. 1, the computing power platform layer includes a "computing power notification" sub-module, and the "computing power notification" sub-module is responsible for notifying the computing power resources actually deployed to the corresponding computing power network element nodes together with information such as a computing power service contract after the computing power resources are abstractly represented by a computing power template. The sub-modules comprise sub-functional modules of computing power service contract announcement, computing power capability announcement, computing power state announcement and the like. The computing power service contract notification means that computing power service requirements are generated according to service requests of the computing power service layer and are notified to corresponding computing power network element nodes. The calculation capacity notification means that after the calculation resources are actually deployed and are abstractly represented by the calculation capacity template, the calculation capacity notification is notified to the corresponding calculation capacity network element nodes. The computing power state notification notifies the real-time state of the computing power resource to a corresponding network node through an I4 interface.
Further, the second processing layer is further configured to:
and performing performance monitoring on the state information of the computing resources of the computing network element nodes, and sending at least one of the performance of the computing resources, the computing cost management information and the computing resource fault information to the corresponding computing network element nodes.
As shown in fig. 1, the second processing layer (i.e., the computing power platform layer) includes "computing power OAM" sub-modules, which include computing power performance monitoring, computing power charge management, and computing power resource fault management for the computing power resource layer. In other words, the computation OAM submodule mainly includes real-time states of the computation network element node, including capacity expansion, capacity reduction and fault states, and according to these information, the computation platform layer can update the current available computation state in time on the one hand, and can perform some operations of fault recovery on the other hand: for example, the computing platform layer sends some operation instructions such as restart and configuration, and the like, and recovers and processes the fault.
As an optional embodiment, the computing power resource status information includes at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
As another optional embodiment, the sending, by the fourth processing layer, the computing resource state information to the second processing layer includes:
and the second processing layer sends a calculation force measurement request message to the fourth processing layer and receives a calculation force state information response message fed back by the fourth processing layer, wherein the calculation force state information response message carries calculation force resource state information of calculation force network element nodes.
For example, as shown in fig. 2, in actual deployment, the second processing layer is deployed on the force calculation management device, and the fourth processing layer is deployed on the force calculation node device, then the force calculation management device actively sends a force calculation measurement request message to the force calculation node device, and the force calculation node device sends a force calculation state information response message to the force calculation management device according to the force calculation measurement request message.
Or, the fourth processing layer sends the computing resource state information to the second processing layer, including:
and the fourth processing layer reports the computing resource state information of the computing network element node to the second processing layer periodically or non-periodically.
Optionally, the computation power measurement request message includes at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
And the second processing layer carries the calculation force measurement request message through the telemetering (telemeasure) information of the operation maintenance management OAM, so that the calculation force sensing work flow is realized.
For example, as shown in fig. 3, unused bits (bit bits) in the telemetry information (e.g., OAM-trace-type) of the OAM are utilized: bit 4-7;
and (7) Bit 7: defined as a bit to indicate whether the power sensing function is on.
And (4) Bit 4: defined as bit of the computation force measurement request/computation force state information response.
And (5) Bit 5: defined as bit of the computation force measurement request/computation force state information response.
For another example, a Node data list (Node data list) is used to carry state information of computational power resources, network resources and the like of the computational power network element Node for the variable length list. Wherein, the calculation power resource means: server, processing, memory, storage, virtual machine, etc. Network resources include network bandwidth, latency, jitter, etc. requirements.
The system for computing network convergence provided by the embodiment of the invention not only defines functional modules such as a computing resource layer, a computing platform layer, a computing routing layer and the like, but also defines interfaces among partial functional modules.
As shown in fig. 1:
i1 interface: an interface between the computing power service layer and the computing power platform layer is defined for communicating SLA (service level agreement) requirements, computing power service deployment configuration information, and the like.
I2 interface: and the calculation force modeling submodule is used for transmitting information such as a calculation force service contract and a calculation force capability template to the calculation force notification submodule.
I3 interface: and the calculation power OAM sub-module is used for transmitting information such as calculation power resource performance monitoring, calculation power charge management, calculation power resource faults and the like to the calculation power notification sub-module.
I4 interface: the method is used for transmitting the computing power service contract information and the state announcement of the computing power resource to the computing power routing layer by the computing power platform layer.
I5 interface: the interface between the calculation power resource layer and the calculation power platform layer is mainly used for calculation power resource registration management, performance state and fault information transmission of calculation power resources and the like.
To sum up, the system for computing network convergence provided by the embodiment of the present invention is a novel network architecture, and based on ubiquitous network connection, based on highly distributed computing nodes, through automatic deployment, optimal routing, and load balancing of services, a completely new network infrastructure for computing power perception is constructed, so that network unavailability, computing power ubiquity, and intelligence unavailability are really realized. The massive applications, the massive function functions and the massive computing resources form an open ecology, wherein the massive applications can call the computing resources in different places in real time according to needs, the utilization efficiency of the computing resources is improved, and finally, the user experience optimization, the computing resource utilization rate optimization and the network efficiency optimization are realized.
As shown in fig. 4, an embodiment of the present invention further provides a computing power processing method applied to a network system for computing power processing, including:
And 43, selecting a corresponding network path at least according to the computing power configuration strategy, and scheduling the service to a corresponding computing power network element node for processing.
Optionally, the method further comprises:
acquiring network resource information;
and selecting a corresponding network path at least according to the computing power configuration strategy and the network resource information, and scheduling the service to a corresponding computing power network element node for processing.
It should be noted that the third processing layer may periodically or dynamically acquire the network resource information from the network resource layer in fig. 1, or the network resource layer actively reports the network resource information, so that the third processing layer can select a corresponding network path according to the computational power configuration policy and the current network resource information, and schedule the service to a corresponding computational power network element node for processing. The current network resource information may be understood as network resource information newly acquired by the third processing layer or network resource information newly reported by the network resource layer.
Optionally, the network path selected by the third processing layer is a current optimal network path, and the computational power network element node scheduled by the third processing layer is the current optimal computational power network element node, which is not specifically limited herein.
Alternatively, the computing power processing method is applied to the computing power processing network system as described in fig. 1 to 3, and the execution subjects of the above steps 41, 42, and 43 may be respective corresponding processing layers of the computing power processing network system, for example, step 41 is executed by a first processing layer, step 42 is executed by a second processing layer, and step 43 is executed by a third processing layer.
It should be noted that, the first processing layer, the second processing layer, and the third processing layer are divided according to logic functions, and in actual deployment, each processing layer may be deployed on one device or multiple devices; if the device is deployed on one device, information transmission can be carried out between the processing layers through the internal interface; if the device is deployed on a plurality of devices, information transmission can be realized among all processing layers through signaling interaction. Optionally, the specific names of the first processing layer, the second processing layer, and the third processing layer are not limited in the embodiment of the present invention, and all layer names capable of implementing the corresponding functions are applicable to the embodiment of the present invention.
In the embodiment of the present invention, the scheduling of the service to the corresponding computational element node includes at least two ways:
the first method is as follows: and (3) computing resource scheduling (namely selecting a corresponding network path according to the computing configuration strategy and scheduling the service to a corresponding computing network element node for processing), matching the service and the computing power and scheduling the service to a proper computing node for service processing. That is, computing-based scheduling enables finding the best-purpose serving compute node.
The second method comprises the following steps: computing resource scheduling + network resource scheduling (namely, selecting a corresponding network path according to the computing configuration strategy and the network resource information, and scheduling the service to a corresponding computing network element node for processing); the calculation resource scheduling is combined with the scheduling of the existing network resource information (for example, the network resource information comprises bandwidth, time delay jitter and the like) in the network; the calculation resource scheduling realizes the scheduling of the service to the proper calculation node, and the network resource scheduling can realize the searching of the optimal network path of the target service calculation node. Namely, scheduling based on network and scheduling of computing power (combining computing power resource scheduling and network resources), through the optimal network path, and performing optimal computing power service processing, thereby providing optimal user experience.
As an alternative embodiment, the method further comprises:
acquiring computing resource state information of a computing network element node;
and obtaining the computing power configuration strategy at least according to the service request and the computing power resource state information.
The computing resource state information is used to reflect information such as a ubiquitous computing capability state and a deployment location in a network, and may refer to capabilities of a service connection number, CPU/GPU computing power, a deployment form (physical, virtual), a deployment location (corresponding IP address), a storage capacity, a storage form, and the like, or may refer to computing capabilities abstracted based on the basic computing resources, and is used to reflect currently available computing capabilities of each node of the network and a distributed location and form.
As an alternative embodiment, the method further comprises:
carrying out abstract description and representation on the computing power resource state information to generate a computing power capability template;
and generating a computing power service contract at least according to the computing power capability template and the service request.
The network system for computing power processing in the embodiment of the present invention further includes: and the fourth processing layer (also called as a computing resource layer) is used for realizing the collection and report of the computing resource state information (reported to the second processing layer). The second processing layer abstractly describes and represents the state information of the computing power resource to generate a computing power capability template; and generating a computing power service contract according to the computing power capability template and the service request of the service.
And sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node. For example, the second processing layer first sends the computational capability template and/or the computational service contract to the third processing layer, and the computational capability template and/or the computational service contract is forwarded to the corresponding computational network element node by the third processing layer, or the computational capability template and/or the computational service contract is directly sent to the computational network element node by the second processing layer, where a specific sending path is not limited herein.
Optionally, the computing capability template is mainly used for unifying some information requesting modes between the computing capability processing network system and the user equipment, for example, after the computing capability processing network system receives a service request of a service, the service request is converted into information conforming to a system processing format according to the computing capability template, so as to facilitate subsequent processing; or after the user equipment receives the computing capability template (which can be acquired by the computing capability network element node), before sending the service request, the user equipment converts the relevant information of the service request into information conforming to the system processing format through the computing capability template, so that the subsequent processing of the system is facilitated, and the processing load of the system is reduced.
Optionally, the computing power service contract is mainly used for generating a corresponding computing power service contract according to the user subscription information, and once the user service comes in, the network needs to provide a corresponding computing power service according to the computing power service contract. In addition, after obtaining the computation force service contract, the user equipment may obtain which computation force network element node the user equipment can communicate with, and obtain a charging rule, and the like, which is not specifically limited herein.
It should be noted that, in the above embodiments of the present invention, the term "at least according to" is understood as: in order to make the obtained result accurate, those skilled in the art can refer to other parameters related to calculation power to obtain better parameters based on the common means in the art, which are not enumerated herein.
As yet another alternative embodiment, the method further comprises:
and sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node. For example, the computing power capability template and/or the computing power service contract are/is sent to a third processing layer, and the third processing layer sends the computing power capability template and/or the computing power service contract to a corresponding computing power network element node.
Further, the method further comprises:
and performing performance monitoring on the state information of the computing resources of the computing network element nodes, and sending at least one of the performance of the computing resources, the computing cost management information and the computing resource fault information to the corresponding computing network element nodes.
As an optional embodiment, the computing power resource status information includes at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
In summary, the computing power processing method provided by the embodiment of the invention is based on ubiquitous network connection, and based on highly distributed computing nodes, through automatic deployment, optimal routing and load balancing of services, a brand-new network infrastructure for computing power perception is constructed, so that network inaccessibility, computing power inaccessibility and intelligence inaccessibility are really realized. The massive applications, the massive function functions and the massive computing resources form an open ecology, wherein the massive applications can call the computing resources in different places in real time according to needs, the utilization efficiency of the computing resources is improved, and finally, the user experience optimization, the computing resource utilization rate optimization and the network efficiency optimization are realized.
The embodiment of the present invention further provides a network system for computing power, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements each process in the embodiment of the computing power processing method when executing the program, and can achieve the same technical effect, and details are not repeated here to avoid repetition.
The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements each process in the above-described computing power processing method embodiment, and can achieve the same technical effect, and details are not repeated here to avoid repetition. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block or blocks.
These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (20)
1. A computing-power processing network system, comprising:
a first processing layer, a second processing layer and a third processing layer;
the first processing layer is used for acquiring a service request of a service and sending the service request to the second processing layer;
the second processing layer is used for obtaining a calculation force configuration strategy at least according to the service request and sending the calculation force configuration strategy to the third processing layer;
and the third processing layer is used for selecting a corresponding network path at least according to the computing power configuration strategy and dispatching the service to a corresponding computing power network element node for processing.
2. The method of claim 1, wherein the third process layer is further configured to:
acquiring network resource information;
and selecting a corresponding network path at least according to the computing power configuration strategy and the network resource information, and scheduling the service to a corresponding computing power network element node for processing.
3. The system of claim 1 or 2, wherein the computationally processed network system further comprises: a fourth process layer;
the fourth processing layer is used for acquiring computing power resource state information of the computing power network element node and sending the computing power resource state information to the second processing layer;
and the second processing layer obtains the computing power configuration strategy at least according to the service request and the computing power resource state information.
4. The system of claim 3, wherein the second processing layer is further configured to:
carrying out abstract description and representation on the computing power resource state information to generate a computing power capability template;
and generating a computing power service contract at least according to the computing power capability template and the service request.
5. The system of claim 4, wherein the second processing layer is further configured to:
and sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node.
6. The system of claim 3, wherein the second processing layer is further configured to:
and performing performance monitoring on the state information of the computing resources of the computing network element nodes, and sending at least one of the performance of the computing resources, the computing cost management information and the computing resource fault information to the corresponding computing network element nodes.
7. The system of claim 3, wherein the computing resource status information comprises at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
8. The system of claim 3, wherein the fourth processing layer sends the computing resource status information to the second processing layer, comprising:
and the second processing layer sends a calculation force measurement request message to the fourth processing layer and receives a calculation force state information response message fed back by the fourth processing layer, wherein the calculation force state information response message carries calculation force resource state information of calculation force network element nodes.
9. The system of claim 3, wherein the fourth processing layer sends the computing resource status information to the second processing layer, comprising:
and the fourth processing layer reports the computing resource state information of the computing network element node to the second processing layer periodically or non-periodically.
10. The system of claim 8, wherein the computation power measurement request message comprises at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
11. The system according to claim 8, wherein the computational power measurement request message is carried by the second processing layer via telemetry information of operation, maintenance, administration, OAM.
12. A computing power processing method is applied to a network system for computing power processing, and is characterized by comprising the following steps:
acquiring a service request of a service;
obtaining a computing power configuration strategy at least according to the service request mapping;
and selecting a corresponding network path at least according to the computing power configuration strategy, and scheduling the service to a corresponding computing power network element node for processing.
13. The method of claim 12, further comprising:
acquiring network resource information;
and selecting a corresponding network path at least according to the computing power configuration strategy and the network resource information, and scheduling the service to a corresponding computing power network element node for processing.
14. The method according to claim 12 or 13, characterized in that the method further comprises:
acquiring computing resource state information of a computing network element node;
and obtaining the computing power configuration strategy at least according to the service request and the computing power resource state information.
15. The method of claim 14, further comprising:
carrying out abstract description and representation on the computing power resource state information to generate a computing power capability template;
and generating a computing power service contract at least according to the computing power capability template and the service request.
16. The method of claim 14, further comprising:
and sending the computing power capability template and/or the computing power service contract to a corresponding computing power network element node.
17. The method of claim 14, further comprising:
and performing performance monitoring on the state information of the computing resources of the computing network element nodes, and sending at least one of the performance of the computing resources, the computing cost management information and the computing resource fault information to the corresponding computing network element nodes.
18. The method of claim 14, wherein the computing resource status information comprises at least one of:
a service ID;
information of the central processing unit CPU;
the number of service links;
information of the memory;
information of the image processor GPU;
information of the hard disk.
19. A computationally-enabled network system comprising a memory, a processor, and a program stored on the memory and executable on the processor; wherein the processor implements the computational processing method according to any one of claims 12 to 18 when executing the program.
20. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the computational power processing method according to any one of claims 12 to 18.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010232182.0A CN113448721A (en) | 2020-03-27 | 2020-03-27 | Network system for computing power processing and computing power processing method |
| PCT/CN2021/082304 WO2021190482A1 (en) | 2020-03-27 | 2021-03-23 | Computing power processing network system and computing power processing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010232182.0A CN113448721A (en) | 2020-03-27 | 2020-03-27 | Network system for computing power processing and computing power processing method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113448721A true CN113448721A (en) | 2021-09-28 |
Family
ID=77808217
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010232182.0A Pending CN113448721A (en) | 2020-03-27 | 2020-03-27 | Network system for computing power processing and computing power processing method |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN113448721A (en) |
| WO (1) | WO2021190482A1 (en) |
Cited By (31)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113867973A (en) * | 2021-12-06 | 2021-12-31 | 腾讯科技（深圳）有限公司 | Resource allocation method and device |
| CN114095964A (en) * | 2021-11-19 | 2022-02-25 | 中国联合网络通信集团有限公司 | A kind of fault recovery method, apparatus and computer readable storage medium |
| CN114090244A (en) * | 2021-11-16 | 2022-02-25 | 中国联合网络通信集团有限公司 | Service arranging method, device, system and storage medium |
| CN114157667A (en) * | 2021-10-28 | 2022-03-08 | 山东浪潮科学研究院有限公司 | Computing power network service system and method facing gateway equipment |
| CN114615180A (en) * | 2022-03-09 | 2022-06-10 | 阿里巴巴达摩院(杭州)科技有限公司 | Calculation force network system, calculation force calling method and device |
| CN114697400A (en) * | 2022-04-13 | 2022-07-01 | 中国电信股份有限公司 | Service scheduling method, system and VTEP |
| CN114756340A (en) * | 2022-03-17 | 2022-07-15 | 中国联合网络通信集团有限公司 | Computing power scheduling system, method, device and storage medium |
| CN115086720A (en) * | 2022-06-14 | 2022-09-20 | 烽火通信科技股份有限公司 | Network path calculation method and device for live broadcast service |
| CN115086230A (en) * | 2022-06-15 | 2022-09-20 | 中国联合网络通信集团有限公司 | Method, device, equipment and storage medium for determining routing of computing network |
| CN115269137A (en) * | 2022-06-21 | 2022-11-01 | 联通(上海)产业互联网有限公司 | Computing power supply node external open service architecture and interface design |
| CN115396514A (en) * | 2022-08-18 | 2022-11-25 | 中国联合网络通信集团有限公司 | Resource allocation method, device and storage medium |
| CN115550370A (en) * | 2022-12-01 | 2022-12-30 | 浩鲸云计算科技股份有限公司 | Computing power resource optimal scheduling allocation method based on multi-factor strategy |
| CN115641173A (en) * | 2022-10-18 | 2023-01-24 | 云迅智能科技南京有限公司 | Application and computing power network fusion method and system and electronic equipment |
| CN115719189A (en) * | 2022-11-21 | 2023-02-28 | 中国联合网络通信集团有限公司 | Material management method, platform, medium and system |
| CN115734291A (en) * | 2022-11-21 | 2023-03-03 | 中国联合网络通信集团有限公司 | Service transmission method, device and storage medium |
| CN115883660A (en) * | 2022-11-21 | 2023-03-31 | 中国联合网络通信集团有限公司 | Industrial production computing power network service method, platform, equipment and medium |
| CN115883268A (en) * | 2022-11-21 | 2023-03-31 | 中国联合网络通信集团有限公司 | Industrial production computing power network service charging method, platform, equipment and medium |
| CN116016537A (en) * | 2022-12-30 | 2023-04-25 | 中国联合网络通信集团有限公司 | Method and device for optimizing selection of computing power network resources |
| CN116232878A (en) * | 2023-01-06 | 2023-06-06 | 中国联合网络通信集团有限公司 | Method, device, equipment and storage medium for configuring computing power network |
| CN116302580A (en) * | 2023-05-25 | 2023-06-23 | 南方电网数字电网研究院有限公司 | Method and device for scheduling calculation force resources of nano relay |
| CN116402318A (en) * | 2023-06-07 | 2023-07-07 | 北京智芯微电子科技有限公司 | Multi-stage computing power resource distribution method and device for power distribution network and network architecture |
| CN116467071A (en) * | 2023-03-22 | 2023-07-21 | 北京神州泰岳软件股份有限公司 | Method and device for sensing computing power in computing power network, storage medium and electronic equipment |
| WO2023217107A1 (en) * | 2022-05-10 | 2023-11-16 | 中国移动通信有限公司研究院 | Communication method and apparatus, and related device and storage medium |
| WO2023225952A1 (en) * | 2022-05-26 | 2023-11-30 | Asiainfo Technologies (China) , Inc. | Resource scheduling method for computing force network |
| WO2023226257A1 (en) * | 2022-05-27 | 2023-11-30 | 量子科技长三角产业创新中心 | Method for determining optimal computing and storage path of computing power network, and monitoring device |
| CN117440046A (en) * | 2023-03-21 | 2024-01-23 | 北京神州泰岳软件股份有限公司 | Data processing method and device for power computing network |
| WO2024045784A1 (en) * | 2022-08-29 | 2024-03-07 | 华为技术有限公司 | Job scheduling method, scheduler, and related device |
| CN118034942A (en) * | 2024-04-12 | 2024-05-14 | 深圳市捷易科技有限公司 | Cluster computing management method, device, equipment and storage medium |
| WO2024104284A1 (en) * | 2022-11-16 | 2024-05-23 | 中国移动通信有限公司研究院 | Nwdaf-based management and decision-making method for computing resources |
| CN119485490A (en) * | 2024-10-23 | 2025-02-18 | 浪潮通信技术有限公司 | Method and system for initiating computing tasks based on 6G industry-specific network-based sensing, computing and intelligence fusion network |
| WO2025065933A1 (en) * | 2023-09-27 | 2025-04-03 | 中国电信股份有限公司技术创新中心 | Method and system for network control in computing-power network scenario, and medium and device |
Families Citing this family (44)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113656187B (en) * | 2021-10-19 | 2021-12-28 | 中通服建设有限公司 | Public security big data computing power service system based on 5G |
| CN114040479B (en) * | 2021-10-29 | 2023-04-28 | 中国联合网络通信集团有限公司 | Method and device for selecting computing power node and computer readable storage medium |
| CN116133128B (en) * | 2021-11-12 | 2025-10-03 | 中国移动通信有限公司研究院 | A service scheduling method, device, communication equipment and storage medium |
| CN114070854B (en) * | 2021-11-26 | 2023-06-27 | 中国联合网络通信集团有限公司 | Method, system, equipment and medium for sensing and routing calculation force in calculation force network |
| CN114780212A (en) * | 2022-01-12 | 2022-07-22 | 青岛图灵科技有限公司 | A Heterogeneous Computing System Based on Layered Architecture |
| CN114745317B (en) * | 2022-02-09 | 2023-02-07 | 北京邮电大学 | Calculation task scheduling method and related equipment for computing power network |
| CN116781732A (en) * | 2022-03-07 | 2023-09-19 | 中国移动通信有限公司研究院 | Routing method, system and node |
| CN114579318B (en) * | 2022-05-06 | 2022-07-29 | 北京智芯微电子科技有限公司 | Resource coordination method, device and equipment for edge computing |
| CN115185763A (en) * | 2022-05-17 | 2022-10-14 | 浙江华云信息科技有限公司 | Alarm engine system based on data collected by IoT |
| CN115118647B (en) * | 2022-05-20 | 2024-02-09 | 北京邮电大学 | Computing power information perception and notification system and method in computing power network |
| CN114979278A (en) * | 2022-05-24 | 2022-08-30 | 深圳点宽网络科技有限公司 | Calculation power scheduling method, device and system based on block chain and electronic equipment |
| CN117170852A (en) * | 2022-05-25 | 2023-12-05 | 北京沃东天骏信息技术有限公司 | Computing power distribution, service and test method, system and storage medium |
| CN115002127A (en) * | 2022-06-09 | 2022-09-02 | 方图智能(深圳)科技集团股份有限公司 | Distributed audio system |
| CN117354220A (en) * | 2022-06-28 | 2024-01-05 | 中兴通讯股份有限公司 | A computing power route search method, device, computing power network node and storage medium |
| CN115113821B (en) * | 2022-07-07 | 2023-05-12 | 北京算讯科技有限公司 | 5G big data power calculation service system based on quantum encryption |
| WO2024036470A1 (en) | 2022-08-16 | 2024-02-22 | Ming Zhongxing | Computing power network system |
| CN115378950B (en) * | 2022-08-16 | 2024-10-01 | 小视科技(江苏)股份有限公司 | Distributed computing power scheduling method and system for edge computing equipment |
| CN117667366A (en) * | 2022-08-24 | 2024-03-08 | 中国电信股份有限公司 | Service processing method, device, electronic equipment and storage medium |
| CN115640121B (en) * | 2022-09-28 | 2024-08-23 | 量子科技长三角产业创新中心 | Hybrid power manipulation method, device, equipment and storage medium |
| CN115297014B (en) * | 2022-09-29 | 2022-12-27 | 浪潮通信信息系统有限公司 | Zero-trust computing network operating system, management method, electronic device and storage medium |
| CN115421930B (en) * | 2022-11-07 | 2023-03-24 | 山东海量信息技术研究院 | Task processing method, system, device, equipment and computer readable storage medium |
| CN115509644B (en) * | 2022-11-21 | 2023-04-28 | 北京邮电大学 | Computing power unloading method, device, electronic device and storage medium |
| CN115729704A (en) * | 2022-11-22 | 2023-03-03 | 中国电信股份有限公司 | Computing resource allocation method, device, and computer-readable storage medium |
| CN116170324B (en) * | 2022-11-30 | 2024-06-11 | 杭州东方通信软件技术有限公司 | Visual view generation method and device suitable for computing power network |
| CN115562843B (en) * | 2022-12-06 | 2023-03-28 | 苏州浪潮智能科技有限公司 | Container cluster computational power scheduling method and related device |
| CN118337649A (en) * | 2023-01-12 | 2024-07-12 | 中兴通讯股份有限公司 | Method for determining calculation force path, electronic device and storage medium |
| CN116048810B (en) * | 2023-02-13 | 2024-08-23 | 量子科技长三角产业创新中心 | Mixed calculation force network identification method and equipment based on three-dimensional view |
| CN116390154B (en) * | 2023-04-10 | 2025-08-26 | 烽火通信科技股份有限公司 | Service carrying method and system in computing power network |
| CN116684418B (en) * | 2023-08-03 | 2023-11-10 | 北京神州泰岳软件股份有限公司 | Calculation power arrangement scheduling method, calculation power network and device based on calculation power service gateway |
| CN116962409B (en) * | 2023-08-16 | 2024-06-25 | 北京信息科技大学 | Industrial Internet system based on intelligent integration of telepathic computing and virtual controller |
| WO2024119887A1 (en) * | 2023-08-18 | 2024-06-13 | Lenovo (Beijing) Limited | Policy and charging control for computing power network |
| CN116760885B (en) * | 2023-08-23 | 2023-10-17 | 亚信科技（中国）有限公司 | Method, device, equipment, medium and program product for managing computing power network business |
| CN116909758B (en) * | 2023-09-13 | 2024-01-26 | 中移(苏州)软件技术有限公司 | Computing task processing methods, devices and electronic equipment |
| CN117240546A (en) * | 2023-09-15 | 2023-12-15 | 中国联合网络通信集团有限公司 | Message processing method, device, equipment and storage medium |
| CN117331700B (en) * | 2023-10-24 | 2024-04-19 | 广州一玛网络科技有限公司 | Computing power network resource scheduling system and method |
| CN117216758B (en) * | 2023-11-08 | 2024-02-23 | 新华三网络信息安全软件有限公司 | Application security detection system and method |
| CN117591388B (en) * | 2023-11-24 | 2024-12-20 | 国网江苏省电力有限公司南通供电分公司 | Power equipment control method and system based on computing power architecture |
| CN117614992B (en) * | 2023-12-21 | 2024-06-25 | 天津建设发展集团股份公司 | Edge decision method and system for engineering remote monitoring |
| CN117648175B (en) * | 2024-01-30 | 2024-04-12 | 之江实验室 | A service execution method, device and electronic device based on dynamic algorithm selection |
| CN118227338B (en) * | 2024-05-22 | 2024-07-26 | 维能(深圳)大数据技术有限公司 | Intelligent power management method and system based on Internet of things |
| CN118227343B (en) * | 2024-05-27 | 2024-07-26 | 浪潮(北京)电子信息产业有限公司 | A data processing method, system, device, equipment, medium and product |
| CN119603710B (en) * | 2024-12-09 | 2025-09-19 | 浪潮通信技术有限公司 | Calculation force sensing method and system of mobile calculation force network |
| CN119991228A (en) * | 2025-01-21 | 2025-05-13 | 中国联合网络通信集团有限公司 | Computing power bidding method and computing power bidding system |
| CN120407209A (en) * | 2025-07-03 | 2025-08-01 | 北京宝联之星科技股份有限公司 | A computing resource management and allocation method, system and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105391651A (en) * | 2015-11-20 | 2016-03-09 | 北京邮电大学 | Virtual optical network multilayer resource convergence method and system |
| CN110266606A (en) * | 2019-07-30 | 2019-09-20 | 中国矿业大学 | Active queue management optimization method and device in edge network |
| CN110719206A (en) * | 2019-10-21 | 2020-01-21 | 中国科学院空间应用工程与技术中心 | Space-based FPGA (field programmable Gate array) virtualization computing service system, method and readable storage medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9396031B2 (en) * | 2013-09-27 | 2016-07-19 | International Business Machines Corporation | Distributed UIMA cluster computing (DUCC) facility |
| CN105321346A (en) * | 2015-09-18 | 2016-02-10 | 成都融创智谷科技有限公司 | Method for utilizing cloud computing basic resource pool to control urban intelligent traffic |
| CN109167835B (en) * | 2018-09-13 | 2021-11-26 | 重庆邮电大学 | Physical resource scheduling method and system based on kubernets |
| CN110213363B (en) * | 2019-05-30 | 2020-12-22 | 华南理工大学 | Cloud resource dynamic allocation system and method based on software-defined network |
-
2020
- 2020-03-27 CN CN202010232182.0A patent/CN113448721A/en active Pending
-
2021
- 2021-03-23 WO PCT/CN2021/082304 patent/WO2021190482A1/en active Application Filing
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105391651A (en) * | 2015-11-20 | 2016-03-09 | 北京邮电大学 | Virtual optical network multilayer resource convergence method and system |
| CN110266606A (en) * | 2019-07-30 | 2019-09-20 | 中国矿业大学 | Active queue management optimization method and device in edge network |
| CN110719206A (en) * | 2019-10-21 | 2020-01-21 | 中国科学院空间应用工程与技术中心 | Space-based FPGA (field programmable Gate array) virtualization computing service system, method and readable storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 于清林: "从边缘计算到算力网络", 《产业科技创新》, 25 January 2020 (2020-01-25), pages 49 - 51 * |
Cited By (46)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114157667A (en) * | 2021-10-28 | 2022-03-08 | 山东浪潮科学研究院有限公司 | Computing power network service system and method facing gateway equipment |
| CN114157667B (en) * | 2021-10-28 | 2023-06-06 | 山东浪潮科学研究院有限公司 | Gateway-device-oriented computing power network service system and method |
| CN114090244B (en) * | 2021-11-16 | 2024-03-19 | 中国联合网络通信集团有限公司 | Service arrangement method, device, system and storage medium |
| CN114090244A (en) * | 2021-11-16 | 2022-02-25 | 中国联合网络通信集团有限公司 | Service arranging method, device, system and storage medium |
| CN114095964A (en) * | 2021-11-19 | 2022-02-25 | 中国联合网络通信集团有限公司 | A kind of fault recovery method, apparatus and computer readable storage medium |
| CN114095964B (en) * | 2021-11-19 | 2023-05-26 | 中国联合网络通信集团有限公司 | Fault recovery method and device and computer readable storage medium |
| CN113867973B (en) * | 2021-12-06 | 2022-02-25 | 腾讯科技（深圳）有限公司 | Resource allocation method and device |
| CN113867973A (en) * | 2021-12-06 | 2021-12-31 | 腾讯科技（深圳）有限公司 | Resource allocation method and device |
| CN114615180A (en) * | 2022-03-09 | 2022-06-10 | 阿里巴巴达摩院(杭州)科技有限公司 | Calculation force network system, calculation force calling method and device |
| CN114756340A (en) * | 2022-03-17 | 2022-07-15 | 中国联合网络通信集团有限公司 | Computing power scheduling system, method, device and storage medium |
| CN114697400A (en) * | 2022-04-13 | 2022-07-01 | 中国电信股份有限公司 | Service scheduling method, system and VTEP |
| CN114697400B (en) * | 2022-04-13 | 2024-08-27 | 中国电信股份有限公司 | Service scheduling method, system and VTEP |
| WO2023217107A1 (en) * | 2022-05-10 | 2023-11-16 | 中国移动通信有限公司研究院 | Communication method and apparatus, and related device and storage medium |
| WO2023225952A1 (en) * | 2022-05-26 | 2023-11-30 | Asiainfo Technologies (China) , Inc. | Resource scheduling method for computing force network |
| WO2023226257A1 (en) * | 2022-05-27 | 2023-11-30 | 量子科技长三角产业创新中心 | Method for determining optimal computing and storage path of computing power network, and monitoring device |
| CN115086720A (en) * | 2022-06-14 | 2022-09-20 | 烽火通信科技股份有限公司 | Network path calculation method and device for live broadcast service |
| CN115086720B (en) * | 2022-06-14 | 2023-06-09 | 烽火通信科技股份有限公司 | Network path calculation method and device for live broadcast service |
| CN115086230A (en) * | 2022-06-15 | 2022-09-20 | 中国联合网络通信集团有限公司 | Method, device, equipment and storage medium for determining routing of computing network |
| CN115269137B (en) * | 2022-06-21 | 2025-09-23 | 联通(上海)产业互联网有限公司 | A computing power supply node open service architecture and interface structure |
| CN115269137A (en) * | 2022-06-21 | 2022-11-01 | 联通(上海)产业互联网有限公司 | Computing power supply node external open service architecture and interface design |
| CN115396514B (en) * | 2022-08-18 | 2023-05-26 | 中国联合网络通信集团有限公司 | Resource allocation method, device and storage medium |
| CN115396514A (en) * | 2022-08-18 | 2022-11-25 | 中国联合网络通信集团有限公司 | Resource allocation method, device and storage medium |
| WO2024045784A1 (en) * | 2022-08-29 | 2024-03-07 | 华为技术有限公司 | Job scheduling method, scheduler, and related device |
| CN115641173A (en) * | 2022-10-18 | 2023-01-24 | 云迅智能科技南京有限公司 | Application and computing power network fusion method and system and electronic equipment |
| WO2024104284A1 (en) * | 2022-11-16 | 2024-05-23 | 中国移动通信有限公司研究院 | Nwdaf-based management and decision-making method for computing resources |
| CN115883660A (en) * | 2022-11-21 | 2023-03-31 | 中国联合网络通信集团有限公司 | Industrial production computing power network service method, platform, equipment and medium |
| CN115883268B (en) * | 2022-11-21 | 2024-07-23 | 中国联合网络通信集团有限公司 | Industrial production computing power network service billing method, platform, equipment and medium |
| CN115883660B (en) * | 2022-11-21 | 2024-10-29 | 中国联合网络通信集团有限公司 | Industrial production computing network service method, platform, equipment and medium |
| CN115719189A (en) * | 2022-11-21 | 2023-02-28 | 中国联合网络通信集团有限公司 | Material management method, platform, medium and system |
| CN115734291A (en) * | 2022-11-21 | 2023-03-03 | 中国联合网络通信集团有限公司 | Service transmission method, device and storage medium |
| CN115883268A (en) * | 2022-11-21 | 2023-03-31 | 中国联合网络通信集团有限公司 | Industrial production computing power network service charging method, platform, equipment and medium |
| CN115550370A (en) * | 2022-12-01 | 2022-12-30 | 浩鲸云计算科技股份有限公司 | Computing power resource optimal scheduling allocation method based on multi-factor strategy |
| CN116016537B (en) * | 2022-12-30 | 2024-03-01 | 中国联合网络通信集团有限公司 | Method and device for optimizing selection of computing power network resources |
| CN116016537A (en) * | 2022-12-30 | 2023-04-25 | 中国联合网络通信集团有限公司 | Method and device for optimizing selection of computing power network resources |
| CN116232878A (en) * | 2023-01-06 | 2023-06-06 | 中国联合网络通信集团有限公司 | Method, device, equipment and storage medium for configuring computing power network |
| CN117440046A (en) * | 2023-03-21 | 2024-01-23 | 北京神州泰岳软件股份有限公司 | Data processing method and device for power computing network |
| CN116467071A (en) * | 2023-03-22 | 2023-07-21 | 北京神州泰岳软件股份有限公司 | Method and device for sensing computing power in computing power network, storage medium and electronic equipment |
| CN116467071B (en) * | 2023-03-22 | 2024-06-07 | 北京神州泰岳软件股份有限公司 | Method and device for sensing computing power in computing power network, storage medium and electronic equipment |
| CN116302580B (en) * | 2023-05-25 | 2023-09-15 | 南方电网数字电网研究院有限公司 | Method and device for scheduling calculation force resources of nano relay |
| CN116302580A (en) * | 2023-05-25 | 2023-06-23 | 南方电网数字电网研究院有限公司 | Method and device for scheduling calculation force resources of nano relay |
| CN116402318B (en) * | 2023-06-07 | 2023-12-01 | 北京智芯微电子科技有限公司 | Multi-stage computing power resource distribution method and device for power distribution network and network architecture |
| CN116402318A (en) * | 2023-06-07 | 2023-07-07 | 北京智芯微电子科技有限公司 | Multi-stage computing power resource distribution method and device for power distribution network and network architecture |
| WO2025065933A1 (en) * | 2023-09-27 | 2025-04-03 | 中国电信股份有限公司技术创新中心 | Method and system for network control in computing-power network scenario, and medium and device |
| CN118034942A (en) * | 2024-04-12 | 2024-05-14 | 深圳市捷易科技有限公司 | Cluster computing management method, device, equipment and storage medium |
| CN118034942B (en) * | 2024-04-12 | 2024-06-25 | 深圳市捷易科技有限公司 | Cluster computing management method, device, equipment and storage medium |
| CN119485490A (en) * | 2024-10-23 | 2025-02-18 | 浪潮通信技术有限公司 | Method and system for initiating computing tasks based on 6G industry-specific network-based sensing, computing and intelligence fusion network |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2021190482A1 (en) | 2021-09-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113448721A (en) | Network system for computing power processing and computing power processing method | |
| CN114095579B (en) | Network system for computing power processing, service processing method and equipment | |
| WO2023284830A1 (en) | Management and scheduling method and apparatus, node, and storage medium | |
| CN103197952B (en) | The management system and method disposed for application system maintenance based on cloud infrastructure | |
| CN114095577A (en) | Resource request method, device, computing power network element node and computing power application device | |
| CN112000448A (en) | Micro-service architecture-based application management method | |
| WO2021233391A1 (en) | Routing information sending method, routing information receiving method, network element and node device | |
| WO2022184094A1 (en) | Network system for processing hash power, and service processing method and hash power network element node | |
| US10680442B2 (en) | Method and system for providing energy services | |
| Arora | Artificial Intelligence-Driven Solutions for Improving Public Safety and National Security Systems | |
| CN115002681A (en) | A computing power perception network and its using method and storage medium | |
| Lei et al. | Computing power network: An interworking architecture of computing and network based on IP extension | |
| CN115297008B (en) | Collaborative training method, device, terminal and storage medium based on intelligent computing network | |
| Tian et al. | An overview of compute first networking | |
| CN115499432B (en) | Household terminal computing power resource management system and computing power resource scheduling method | |
| Maciel et al. | A marketplace-based approach to cloud network slice composition across multiple domains | |
| Apat et al. | Service placement in fog computing environment | |
| CN116938837A (en) | Resource scheduling method, device and equipment | |
| Alqarni et al. | A Survey of Computational Offloading in Cloud/Edge-based Architectures: Strategies, Optimization Models and Challenges. | |
| Bumgardner et al. | Cresco: A distributed agent-based edge computing framework | |
| Abouelela et al. | Multidomain hierarchical resource allocation for grid applications | |
| Herlicq et al. | Nextgenemo: an efficient provisioning of edge-native applications | |
| Hung et al. | A new technique for optimizing resource allocation and data distribution in mobile cloud computing | |
| WO2014036715A1 (en) | System and method for controlling real-time resource supply process based on delivery point | |
| Alghamdi et al. | Fog network area management model for managing fog-cloud resources in IoT Environment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |