WO2015101091A1 - Distributed resource scheduling method and device - Google Patents

Abstract

A distributed resource scheduling method and device. The method comprises: according to predetermined acquisition steps, acquiring a first standard deviation of the resource utilization rates of the same type of service virtual machine in each server in a distributed cluster system; when the first standard deviation is greater than or equal to a scheduling threshold value, conducting balanced scheduling on the same type of service virtual machine in any server in the distributed cluster system to another server in the distributed cluster system; according to the predetermined acquisition steps, reacquiring the second standard deviation of the resource utilization rates of the same type of service virtual machine in each server after the balanced scheduling is conducted; and comparing the second standard deviation acquired after the balanced scheduling is conducted at least one time, and executing the balanced scheduling corresponding to the minimum second standard deviation. By conducting distributed resource scheduling according to the type of the service virtual machine in each server in the distributed cluster system, or according to the proportion of each type of service virtual machine in each server for occupying the resources of the server where the service virtual machine are located, the quality of service of each service virtual machine in each server can be guaranteed.

Description

Distributed resource scheduling method and device

This application claims priority to Chinese Patent Application No. 201310751965.X, filed on Dec. 31, 2013, entitled "Distributed Resource Scheduling Method and Apparatus", the entire contents of which are incorporated by reference. In this application.

Technical field

The present invention relates to resource scheduling technologies, and in particular, to a distributed resource scheduling method and apparatus.

Background technique

In a virtualization or cloud computing solution, each server in a server cluster generally includes multiple virtual machines running different types of services. When different types of services are deployed on the same server, ie, compute nodes, such as a compute node. There are desktop cloud virtual machines and compiled business virtual machines. You need to consider how to ensure the quality of their respective services, ensure that the resources of each virtual machine do not interfere with each other, and maximize the utilization of cluster resources.

In the prior art, Quality of Service (QoS) is used to guarantee the quality of service of different types of services of the same computing node. It requires that the total amount and proportion of different types of virtual machines remain stable, for example, 40 computing nodes. The virtual machine, in which 15 desktop cloud virtual machines are compiled, and 25 cloud virtual machines are compiled. By setting the virtual machine shares to be high, medium, and low, a high share of the virtual machine is obtained to obtain a considerable share of resources; a distributed resource scheduling program (Distributed Resource) is adopted. Scheduler (DRS) maximizes the resource utilization in the cluster. For example, DRS migrates the overloaded virtual machine to a server with low load. At this time, the resource usage of the overloaded virtual machine is improved, and the original server is used. The resource occupancy rate of the virtual machine has also been improved, and the overall resource occupancy rate of the cluster has been improved.

However, after the DRS is started, if the virtual machine is migrated to another server, the proportion of different types of service virtual machines in the server will be unbalanced. Therefore, how to guarantee each service after starting DRS The service quality of each business virtual machine in the device is an urgent problem to be solved.

Summary of the invention

The embodiment of the invention provides a distributed resource scheduling method and device, which can guarantee the service quality of each service virtual machine in each server during distributed resource scheduling.

In a first aspect, a distributed resource scheduling method is provided, including:

Obtaining the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system;

And obtaining, according to the resource usage rate of the service virtual machine of the same type in each server, a first standard deviation of the resource usage rate of the same type of service virtual machine in each server by using a predetermined obtaining step, where the obtaining step is: Acquiring an average resource usage rate of the same type of service virtual machine in each server according to the resource usage rate of the same type of service virtual machine in each server, and according to resource usage of the same type of service virtual machine in each server Rate and the average resource usage rate, obtaining a first standard deviation of resource usage rates of the same type of service virtual machine in each server;

And when the first standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, the distributed cluster is The same type of service virtual machine of any server in the system is balancedly dispatched to other servers of the distributed cluster system;

Obtaining a resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling;

And obtaining the resource usage rate of the same type of service virtual machine in each server by using the predetermined obtaining step according to the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balance scheduling Second standard deviation;

Comparing the second standard deviation acquired after the balanced scheduling at least once, performing the minimum balanced scheduling corresponding to the second standard deviation.

In a first possible implementation manner, the method further compares the second standard deviation acquired after the balanced scheduling at least once, and before performing the balance scheduling corresponding to the minimum second standard deviation, the method further Includes:

The second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the next balanced scheduling is greater than or equal to the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling The second standard deviation, or the next balance scheduling, and the cumulative number of times of the balanced scheduling exceeds the first set threshold, then the performing the obtaining step and the next balancing scheduling are stopped.

In a second aspect, a distributed resource scheduling method is provided, including:

Obtaining a resource usage rate of each server according to a proportion of resources of each server in each server in the distributed cluster system and a resource usage rate of each type of service virtual machine in each server;

Acquiring, according to the resource usage rate of each server, a third standard deviation of the resource usage rate of the distributed cluster system by using a predetermined obtaining step, where the obtaining step is: acquiring the resource according to the resource usage rate of each server The average resource usage of the distributed cluster system, and the third standard deviation of the resource usage rate of the distributed cluster system is obtained according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system;

When the third standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the scheduling threshold of the resource usage rate of the distributed cluster system, balancing any service virtual machine in each server to the In other servers of the distributed cluster system;

Obtaining the resource usage rate of each server in the distributed cluster system after the balanced scheduling;

And obtaining, according to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, the fourth standard deviation of the resource usage rate of the distributed cluster system after the balanced scheduling by using the predetermined obtaining step;

Comparing the fourth standard deviation acquired after the balanced scheduling at least once, performing the minimum balanced scheduling corresponding to the fourth standard deviation.

In a first possible implementation manner, the method further compares the fourth standard deviation acquired after the balanced scheduling at least once, before performing the balance scheduling corresponding to the minimum fourth standard deviation, include:

If the fourth standard deviation of the resource usage rate of the distributed cluster system after the next balanced scheduling is greater than or equal to the resource usage rate of the distributed cluster system after performing the current balanced scheduling The fourth standard deviation, or the next balance scheduling, after the cumulative number of the balanced scheduling exceeds the first set threshold, or after the service virtual machine is balancedly dispatched from any first server to any second server, The change in the total amount of each type of service virtual machine in any one of the first servers or any of the second servers is greater than a second set threshold, and/or any of the first servers or any of the second If the change of the resources of the first service server in the server is greater than the third set threshold, the obtaining step and the next balanced scheduling are stopped.

In a third aspect, a distributed resource scheduling apparatus is provided, including:

a first acquiring unit, configured to acquire resource usage rates of the same type of service virtual machines in each server in the distributed cluster system;

a second acquiring unit, configured to acquire, according to a resource usage rate of the same type of service virtual machine in each server, a first standard deviation of resource usage rates of the same type of service virtual machine in each server by using a predetermined acquisition manner Obtaining, according to the resource usage rate of the same type of service virtual machine in each server, obtaining an average resource usage rate of the same type of service virtual machine in each server, and according to the same in each server The resource usage rate of the type service virtual machine and the average resource usage rate, and obtaining a first standard deviation of resource usage rates of the same type of service virtual machine in each server;

a first scheduling unit, configured to: when a first standard deviation of resource usage rates of the same type of service virtual machines in the servers is greater than or equal to a scheduling threshold of resource usage rates of the same type of service virtual machines in each server And balancing the same type of service virtual machines of any one of the servers in the distributed cluster system to other servers of the distributed cluster system;

a third acquiring unit, configured to obtain resource usage rates of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling;

a fourth acquiring unit, configured to acquire, according to the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system, the same type in each server The second standard deviation of the resource usage of the business virtual machine;

a first comparing unit, configured to compare the second standard deviation acquired after the balancing scheduling at least once;

a first execution unit, configured to perform the balance scheduling corresponding to the minimum of the second standard deviation.

In a first possible implementation, the first execution unit is further configured to:

The second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the next balanced scheduling is greater than or equal to the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling The second standard deviation of the second type, or the next balance scheduling, if the cumulative number of the balanced scheduling exceeds the first set threshold, the second criterion for stopping the resource utilization rate of the same type of service virtual machine in each server is stopped. Poor acquisition and next balanced scheduling.

In a fourth aspect, a distributed resource scheduling apparatus is provided, including:

a fifth obtaining unit, configured to acquire, according to a proportion of resources of each type of service virtual machines in each server in the distributed cluster system, and a resource usage rate of each type of service virtual machine in each server, Server resource usage rate;

a sixth obtaining unit, configured to acquire, according to the resource usage rate of each server, a third standard deviation of the resource usage rate of the distributed cluster system by using a predetermined acquisition manner, where the obtaining manner is: according to each server The resource usage rate obtains the average resource usage rate of the distributed cluster system, and acquires resource usage of the distributed cluster system according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system. The third standard deviation of the rate;

a second scheduling unit, configured to: when the third standard deviation of resource usage of the distributed cluster system is greater than or equal to a scheduling threshold of resource usage of the distributed cluster system, any service in each server Virtual machine balancing is dispatched to other servers of the distributed cluster system;

a seventh acquiring unit, configured to obtain resource usage rates of servers in the distributed cluster system after the balanced scheduling;

An eighth obtaining unit, configured to acquire, according to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, the fourth standard of resource utilization rate of the distributed cluster system after the balanced scheduling by using the predetermined acquiring manner difference;

a second comparing unit, configured to compare the fourth standard deviation acquired after the balanced scheduling at least once;

a second execution unit, configured to perform the balance scheduling corresponding to the minimum of the fourth standard deviation.

In a first possible implementation, the second execution unit is further configured to:

If the fourth standard deviation of the resource usage rate of the distributed cluster system after the next balanced scheduling is greater than or equal to the fourth standard deviation of the resource usage rate of the distributed cluster system after the current balancing scheduling, or the next time Balanced scheduling, after the cumulative number of times of the balanced scheduling exceeds a first set threshold, or after the service virtual machine is balancedly dispatched from any first server to any second server, any of the first servers or offices The change of the total amount of the service virtual machines in any of the second servers is greater than the second set threshold, and/or the service virtual machines occupying any of the first servers or any of the second servers If the change of the resources of any of the first servers is greater than the third set threshold, the resource usage rate acquisition and the next balanced scheduling of the distributed cluster system after the balanced scheduling are stopped.

The technical solution of the distributed resource scheduling method and device provided by the embodiment of the present invention is adopted according to the type of the service virtual machine in each server in the distributed cluster system, or according to the server of the various service virtual machines in each server. The proportion of resources is distributed resource scheduling, which can guarantee the service quality of each service virtual machine in each server.

DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below. Obviously, the drawings in the following description are only It is a certain embodiment of the present invention, and other drawings can be obtained from those skilled in the art without any creative work.

FIG. 1 is a schematic flowchart of a distributed resource scheduling method according to an embodiment of the present disclosure;

2 is a schematic flowchart of another distributed resource scheduling method according to an embodiment of the present invention;

FIG. 3 is a schematic flowchart of still another distributed resource scheduling method according to an embodiment of the present disclosure;

FIG. 4 is a schematic flowchart diagram of still another distributed resource scheduling method according to an embodiment of the present disclosure;

FIG. 5 is a schematic structural diagram of a distributed resource scheduling apparatus according to an embodiment of the present disclosure;

FIG. 6 is a schematic structural diagram of another distributed resource scheduling apparatus according to an embodiment of the present disclosure;

FIG. 7 is a schematic structural diagram of a distributed resource scheduling device according to an embodiment of the present disclosure;

FIG. 8 is a schematic structural diagram of another distributed resource scheduling device according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.

FIG. 1 is a schematic flowchart diagram of a distributed resource scheduling method according to an embodiment of the present invention. The method includes the following steps:

Step S101: Obtain a resource usage rate of a service virtual machine of the same type in each server in the distributed cluster system.

A server cluster of virtualization or cloud computing includes multiple servers, each of which includes multiple virtual machines, which can run different types of services, called business virtual machines. The DRS technology is used to allocate resources of the server cluster. The system allocates certain resources to each server, and each server allocates corresponding resources to each virtual machine. Therefore, the server cluster is also called a distributed cluster system, and the resources here are Refers to central processing unit (CPU), memory, and input/output (I/O) control, storage, and input/output resources.

In this step, the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system is obtained by acquiring a monitor in each server, and the monitor monitors the type of service virtual in the server. The resource usage rate of the device is reported to the DRS, or the DRS requests the monitor to use the resource usage rate of the virtual machine of the type. The number of times the resource usage rate of the service virtual machine of the type is obtained from the monitor may be one time or multiple times. . The resource usage rate herein may be a usage rate of a certain resource, or may be a weighted value of resource usage rates of various resources such as CPU, memory, and I/O.

Each of the servers in the distributed cluster system has one or more types of service virtual machines, for example, a desktop cloud virtual machine and a compiled cloud virtual machine. In this embodiment, resources of the same type of virtual machine in each server are respectively obtained according to the service type. Usage rate.

For example, there are three servers in the cluster. There are two desktop cloud virtual machines and two virtual cloud virtual machines in the server 1. There are three desktop cloud virtual machines, two virtual cloud virtual machines, and a desktop cloud in the server 3. One virtual machine and two virtual machines are compiled. DRS allocates certain CPU, memory and I/O resources to the servers 1, 2 and 3 in the cluster. Each server allocates certain internal virtual machines. For CPU, memory, and I/O resources, taking CPU resource allocation as an example, DRS allocates CPU resources of number A to server 1, allocates CPU resources of quantity B to server 2, and allocates CPU resources of number C to server 3. The server 1 allocates CPU resources of A1, A2, A3, and A4 to the two desktop cloud virtual machines and the two compiled cloud virtual machines respectively, and takes the resource usage rate of the desktop cloud virtual machine as an example, and two in the server 1 The resource utilization rate of the desktop cloud virtual machine is 30% and 40%, respectively, and the resource utilization rate of the CPU of the desktop cloud virtual machine in the server 1 is (30%*A1+40%*A2)/(A1+A2), Then calculate the total memory of the desktop cloud virtual machine in server 1 in the same way. And the resource usage rate of the I/O, and then the total CPU, memory, and I/O resource usage rate are weighted, and the resource usage rate of the desktop cloud virtual machine of the server 1 is obtained, and the servers 2 and 3 are obtained by analogy. Resource usage of the desktop cloud virtual machine. At the same time, the resource usage rate of the compiled cloud virtual machine in each server can also be obtained in the same manner.

Step S102: Acquire, according to a resource usage rate of the same type of service virtual machine in each server, a first standard deviation of resource usage rates of the same type of service virtual machine in each server by using a predetermined obtaining step, where the obtaining The step is: obtaining an average resource usage rate of the same type of service virtual machine in each server according to the resource usage rate of the same type of service virtual machine in each server, and according to the same type of service virtual machine in each server The resource usage rate and the average resource usage rate obtain a first standard deviation of resource usage rates of the same type of service virtual machine in each server.

The DRS technology is used to ensure the maximum resource utilization in the cluster. Therefore, the standard deviation between the resource usage rate of the same type of service virtual machine in each server in the cluster and the average resource usage rate of the same type of service virtual machine in each server is calculated. The standard deviation is used for the degree of dispersion of the reaction data, and its calculation formula is as shown in formula (1):

In formula (1), x _i is the resource usage rate of the same type of service virtual machine in each server; μ is the average resource usage rate of the same type of service virtual machine in each server, and N is the number of servers in the cluster. σ is the standard deviation.

According to the standard deviation acquisition step, it is first necessary to obtain the average resource usage rate of the same type of service virtual machine in each server. The resource usage rate of the same type of service virtual machine in each server has been obtained in step S101, and the average resource usage rate of the same type of service virtual machine in each server can be obtained according to the existing calculation manner. For example, in the previous example, if there are three servers, the resource usage rate of the same type of service virtual machine in each server is obtained and divided by the number of servers, that is, the average resource usage rate is obtained.

Then, according to formula (1), the standard deviation of resource utilization rates of the same type of service virtual machine in each server is obtained.

Step S103, when the first standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, The same type of service virtual machine of any server in the distributed cluster system is balancedly dispatched to other servers of the distributed cluster system.

By comparing the obtained standard deviation with the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, the system can determine whether the resource usage of the type of service virtual machine in each server is unbalanced, and the larger the standard deviation, the imbalance rate is indicated. The higher. It should be noted that, since there are multiple types of service virtual machines in each server, the standard deviation of the average resource usage rate obtained from each of the same types of service virtual machines in each server is calculated, and the standard deviation obtained is obtained. The result may be that the resource usage of one type of business virtual machine is balanced, while the resource usage of another type of business virtual machine is out of balance.

The scheduling is triggered when the first standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server. During the scheduling process, the recursive scheduling process may be performed in a recursive scheduling process by balancing the same type of service virtual machines of any server in the distributed cluster system to other servers of the distributed cluster system.

Step S104: The resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling is obtained.

Step S105, according to the foregoing in each server in the distributed cluster system after the balanced scheduling The resource usage rate of the service virtual machine of the same type is obtained by the predetermined obtaining step, and the second standard deviation of the resource usage rate of the same type of service virtual machine in each server is obtained.

After each round of balanced scheduling, the impact of the scheduling virtual machine on the imbalance rate is obtained, that is, the standard deviation of the resource usage rate of the same type of service virtual machine in each server after the balanced scheduling is re-acquired.

After each round of balanced scheduling, the resource usage rate of the same type of service virtual machine in each server changes, firstly, the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling is obtained. Then, according to the predetermined standard deviation obtaining step, the standard deviation of the resource usage rate of the same type of service virtual machine in each server after the round balancing scheduling is obtained.

Step S106: Compare the second standard deviation acquired after the balanced scheduling at least once, and perform the minimum balanced scheduling corresponding to the second standard deviation.

A plurality of rounds of the above-mentioned balanced scheduling may be performed, and a certain policy may be used for scheduling, for example, the overloaded service virtual machine is scheduled to other servers, which is not limited in the embodiment of the present invention. The standard deviation of the resource usage rate of the same type of service virtual machine in each server after the round-balanced scheduling obtained by each round of balanced scheduling, and then comparing the multiple standard deviations obtained after multiple rounds of balanced scheduling, and selecting the minimum standard deviation, Finally, the balanced scheduling corresponding to the minimum standard deviation is performed, that is, the balance scheduling obtained by acquiring the minimum standard deviation is to which one or which virtual machines are scheduled to which server or servers, and the balancing scheduling is performed.

It should be noted that, because distributed resource scheduling is performed for the same type of service virtual machine in each server, distributed resource scheduling of each type of service virtual machine in each server may be separately performed, if resources of a certain type of service virtual machine The distributed resource scheduling is performed using equalization.

It can be seen that, according to the distributed resource scheduling method provided by the embodiment of the present invention, the distributed resource scheduling according to the type of the service virtual machine in each server in the distributed cluster system can ensure the service quality of each service virtual machine in each server. .

FIG. 2 is a schematic flowchart diagram of another distributed resource scheduling method according to an embodiment of the present invention. The method is different from the previous embodiment in that step S206 is further included: if the resource usage rate of the same type of service virtual machine in each server is performed after the next balanced scheduling is performed The second standard deviation is greater than or equal to the second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling, or the next balancing schedule is performed, and the cumulative number of the balanced scheduling is exceeded. Once the threshold is set, the acquisition step and the next balanced scheduling are stopped.

Recursive scheduling is used to make the scheduling efficiency the highest, and the recursive exit condition is set in the recursive scheduling, that is, the second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the next balanced scheduling is greater than or equal to Performing the second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling, or ending the next balancing scheduling, and stopping the cumulative number of the balancing scheduling exceeding the first set threshold, then stopping The acquisition step and the next balanced scheduling are performed. This helps to stop the above acquisition steps and balance scheduling in time, obtain the minimum standard deviation, and perform the balanced scheduling corresponding to the minimum standard deviation.

FIG. 3 is a schematic flowchart diagram of still another distributed resource scheduling method according to an embodiment of the present invention. The method includes the following steps:

Step S301: Acquire resource usage of each server according to a proportion of resources of each server in each server in the distributed cluster system, and a resource usage rate of each type of service virtual machine in each server. rate.

In a distributed cluster system, there are one or more types of service virtual machines in each server. For example, there are desktop cloud virtual machines and compiled cloud virtual machines. DRS allocates certain operations, storage, and input/output to each server in the cluster. Resources, each server allocates the resources it obtains to its internal types of business virtual machines in a certain proportion. Ensure that the total amount and proportion of resources of different types of service virtual machines in each server remain stable, and the service quality of various service virtual machines in each server can be guaranteed.

For example, there are three servers in the cluster. There are two desktop cloud virtual machines and two virtual cloud virtual machines in the server 1. There are three desktop cloud virtual machines, two virtual cloud virtual machines, and a desktop cloud in the server 3. One virtual machine and two virtual machines are compiled. The DRS allocates certain CPU, memory, and I/O resources to the servers 1, 2, and 3 in the cluster. Each server allocates a certain CPU to each internal virtual machine. For example, the CPU and the I/O resources are allocated to the CPU 1 by the DRS. The DRS allocates the CPU resources of the number A to the server 1 and allocates the quantity B to the server 2. CPU resources are allocated to the server 3 with a CPU resource of C. The server 1 allocates CPU resources of A1, A2, A3, and A4 to the two desktop cloud virtual machines and the two compiled cloud virtual machines respectively. The resource utilization rate of the desktop cloud virtual machine is 30% and 40% respectively, and the resource utilization rates of the two compiled cloud virtual machines in the server 1 are 40% and 50%, respectively, and the resource utilization rate of the CPU of the server 1 is obtained ( 30%*A1+40%*A2+40%*A3+50%A4)/(A1+A2+A3+A4), and then calculate the memory and I/ of each type of virtual machine in server 1 in the same way. The resource usage rate of O is weighted by the CPU, memory, and I/O resource usage of the server 1, and the resource usage rate of the server 1 is obtained, and the calculations of the servers 2 and 3 are deduced by analogy.

Step S302: Obtain a third standard deviation of the resource usage rate of the distributed cluster system by using a predetermined acquisition step according to the resource usage rate of each server, where the obtaining step is: according to the resource usage rate of each server Acquiring an average resource usage rate of the distributed cluster system, and acquiring a third resource utilization rate of the distributed cluster system according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system. Standard deviation.

The difference from the foregoing embodiment is that, for all kinds of service virtual machines in each server, the resource usage rate of each server and the average resource usage rate of the entire distributed cluster system are obtained in the same manner as the foregoing embodiment, and then According to formula (1), the standard deviation of resource utilization rate of the distributed cluster system is obtained.

Step S303, when the third standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the scheduling threshold of the resource usage rate of the distributed cluster system, balance scheduling of any service virtual machine in each server. To other servers in the distributed cluster system.

Comparing the standard deviation of the resource usage rate of the obtained distributed cluster system with the scheduling threshold of the resource usage rate of the distributed cluster system, if the standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the distributed cluster The scheduling threshold of the system's resource usage triggers balanced scheduling. The object of balanced scheduling can be any business virtual machine in each server.

Step S304, the resource usage rate of each server in the distributed cluster system after the balanced scheduling is obtained.

Step S305: According to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, obtain the fourth standard deviation of the resource usage rate of the distributed cluster system after the balanced scheduling by using the predetermined obtaining step.

Step S306, comparing the fourth standard deviation acquired after the balanced scheduling at least once, and performing the minimum balanced scheduling corresponding to the fourth standard deviation.

Step S304-step S306 is similar to step S104-step S106 of the foregoing embodiment, and is not described here again. The difference is that, for each type of service virtual machine in each server, the obtained distributed cluster system is obtained. The standard deviation of resource usage.

It can be seen that, according to the distributed resource scheduling method provided by the embodiment of the present invention, distributed resource scheduling can be performed according to the ratio of the resources of the servers in which the various service virtual machines occupy the server, so that the services of the service virtual machines in each server can be guaranteed. quality.

FIG. 4 is a schematic flowchart diagram of still another distributed resource scheduling method according to an embodiment of the present invention. The method is different from the previous embodiment in that step S406 is further included: the fourth standard deviation of the resource usage rate of the distributed cluster system after the next balanced scheduling is greater than or equal to the distribution after the current balancing scheduling is performed. The fourth standard deviation of the resource usage rate of the cluster system, or the next balanced scheduling, the cumulative number of the balanced scheduling exceeds the first set threshold, or the service virtual machine is balancedly scheduled from any first server. After any second server, the total amount of the various service virtual machines in any one of the first servers or any of the second servers is greater than a second set threshold, and/or any of the first If the change of the resources of the first service server of the server or the any of the second servers is greater than the third set threshold, the obtaining step and the next balanced scheduling are stopped.

Recursive scheduling can be used to make the scheduling efficiency the highest, and the recursive exit condition is set in the recursive scheduling. That is, after the next balanced scheduling, the fourth standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the current balancing scheduling. The fourth standard deviation of the resource usage rate of the distributed cluster system, or the next balanced scheduling, the cumulative number of times of the balanced scheduling exceeds a first set threshold, or the service virtual machine is from any first After the server balances the scheduling to any of the second servers, the total amount of the various service virtual machines in any one of the first servers or any of the second servers is greater than a second set threshold, and/or the Stopping the obtaining step and the next balancing when the change of the resources of the first server or the any of the second servers in the first server is greater than the third set threshold. Scheduling. This helps to stop the above acquisition steps and balance scheduling in time, to obtain the minimum standard deviation, and to perform the minimum The standard deviation corresponds to the balanced scheduling.

FIG. 5 is a schematic structural diagram of a distributed resource scheduling apparatus according to an embodiment of the present invention. The device 1000 includes:

The first obtaining unit 11 is configured to acquire resource usage rates of the same type of service virtual machines in each server in the distributed cluster system.

A server cluster of virtualization or cloud computing includes multiple servers, each of which includes multiple virtual machines, which can run different types of services, called business virtual machines. The DRS technology is used to allocate resources of the server cluster. The system allocates certain resources to each server, and each server allocates corresponding resources to each virtual machine. Therefore, the server cluster is also called a distributed cluster system, and the resources here are Refers to central processing unit (CPU), memory, and input/output (I/O) control, storage, and input/output resources.

The first obtaining unit 11 obtains the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system, and the obtaining manner may be: setting a monitor in each server, and the monitor monitoring the type of service virtual in the server The resource usage rate of the device is reported to the DRS, or the DRS requests the monitor to use the resource usage rate of the virtual machine of the type. The number of times the resource usage rate of the service virtual machine of the type is obtained from the monitor may be one time or multiple times. . The resource usage rate herein may be a usage rate of a certain resource, or may be a weighted value of resource usage rates of various resources such as CPU, memory, and I/O.

Each of the servers in the distributed cluster system has one or more types of service virtual machines, for example, a desktop cloud virtual machine and a compiled cloud virtual machine. In this embodiment, resources of the same type of virtual machine in each server are respectively obtained according to the service type. Usage rate.

For example, there are three servers in the cluster. There are two desktop cloud virtual machines and two virtual cloud virtual machines in the server 1. There are three desktop cloud virtual machines, two virtual cloud virtual machines, and a desktop cloud in the server 3. One virtual machine and two virtual machines are compiled. DRS allocates certain CPU, memory and I/O resources to the servers 1, 2 and 3 in the cluster. Each server allocates certain internal virtual machines. CPU, memory, and I/O resources. Taking CPU resource allocation as an example, DRS allocates CPU resources of number A to server 1, and allocates the number of servers to server 2. CPU resources of B, allocate CPU resources of C to server 3, and server 1 allocates CPU resources of A1, A2, A3, and A4 to the two desktop cloud virtual machines and two compiled cloud virtual machines respectively. For example, the resource usage rate of the cloud virtual machine in the server 1 is 30% and 40% respectively, and the resource utilization rate of the CPU of the desktop cloud virtual machine in the server 1 is obtained (30%). *A1+40%*A2)/(A1+A2), and then calculate the total memory and I/O resource usage rate of the desktop cloud virtual machine in server 1 in the same way, and then the total CPU and memory. The resource usage rate of the I/O is weighted, the resource usage rate of the desktop cloud virtual machine of the server 1 is obtained, and the resource usage rate of the desktop cloud virtual machine of the servers 2 and 3 is obtained by analogy. At the same time, the resource usage rate of the compiled cloud virtual machine in each server can also be obtained in the same manner.

The second obtaining unit 12 is configured to acquire, according to a resource usage rate of the same type of service virtual machine in each server, a first standard of resource utilization rate of the same type of service virtual machine in each server by using a predetermined acquisition manner. The obtaining manner is: obtaining an average resource usage rate of the same type of service virtual machine in each server according to a resource usage rate of the same type of service virtual machine in each server, and according to the The resource usage rate of the same type of service virtual machine and the average resource usage rate obtain the first standard deviation of the resource usage rate of the same type of service virtual machine in each server.

The DRS technology is used to ensure the maximum resource utilization in the cluster. Therefore, the second obtaining unit 12 obtains the resource usage rate of the same type of service virtual machine in each server in the cluster and the average resource usage of the same type of service virtual machine in each server. The standard deviation of the rate, the standard deviation is used for the degree of dispersion of the reaction data, and the calculation formula is as shown in the formula (1).

According to the calculation formula of the standard deviation, the second obtaining unit 12 first needs to obtain the average resource usage rate of the same type of service virtual machine in each server. The first obtaining unit 11 has acquired the resource usage rate of the same type of service virtual machine in each server, and the second obtaining unit 12 can obtain the average resource usage rate of the same type of service virtual machine in each server according to the existing calculation manner. For example, in the previous example, if there are three servers, the resource usage rate of the same type of service virtual machine in each server is obtained and divided by the number of servers, that is, the average resource usage rate is obtained.

Then, the second obtaining unit 12 obtains the same type of service virtuality in each server according to formula (1). The standard deviation of the resource utilization rate of the proposed machine.

The first scheduling unit 13 is configured to: when a first standard deviation of resource usage rates of the same type of service virtual machines in the servers is greater than or equal to a scheduling threshold of resource usage rates of the same type of service virtual machines in the servers The same type of service virtual machine of any one of the servers in the distributed cluster system is balancedly dispatched to other servers of the distributed cluster system.

By comparing the obtained standard deviation with the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, the system can determine whether the resource usage of the type of service virtual machine in each server is unbalanced, and the larger the standard deviation, the imbalance rate is indicated. The higher. It should be noted that, since there are multiple types of service virtual machines in each server, the standard deviation of the average resource usage rate obtained from each of the same types of service virtual machines in each server is calculated, and the standard deviation obtained is obtained. The result may be that the resource usage of one type of business virtual machine is balanced, while the resource usage of another type of business virtual machine is out of balance.

When the first standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, the first scheduling unit 13 triggers Scheduling. During the scheduling process, the recursive scheduling process may be performed in a recursive scheduling process by balancing the same type of service virtual machines of any server in the distributed cluster system to other servers of the distributed cluster system.

The third obtaining unit 14 is configured to obtain resource usage rates of the same type of service virtual machines in each server in the distributed cluster system after the balanced scheduling.

The fourth obtaining unit 15 is configured to acquire, according to the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system, the same acquisition manner to obtain the same in each server. The second standard deviation of resource usage for a type of business virtual machine.

After each round of balancing, the fourth obtaining unit 15 acquires the influence of the scheduling virtual machine on the imbalance rate, that is, the fourth obtaining unit 15 re-acquires the standard deviation of the resource usage rate of the same type of service virtual machine in each server after the balanced scheduling.

After each round of balanced scheduling, the resource usage rate of the same type of service virtual machine in each server changes. First, the third obtaining unit 14 acquires the same type of service virtuality in each server in the distributed cluster system after the balanced scheduling. The resource usage rate of the machine, and then the fourth obtaining unit 15 acquires the same in each server after the round balance scheduling according to the predetermined standard deviation acquisition manner. The standard deviation of resource usage for a type of business virtual machine.

a first comparing unit 16, configured to compare the second standard deviation acquired after the balancing scheduling at least once;

The first executing unit 17 is configured to perform the balance scheduling corresponding to the minimum of the second standard deviation.

A plurality of rounds of the above-mentioned balanced scheduling may be performed, and a certain policy may be used for scheduling, for example, the overloaded service virtual machine is scheduled to other servers, which is not limited in the embodiment of the present invention. The standard deviation of the resource usage rate of the same type of service virtual machine in each server after the round-balanced scheduling obtained by each round of balanced scheduling, and then comparing the multiple standard deviations obtained after multiple rounds of balanced scheduling, and selecting the minimum standard deviation, The first execution unit 17 finally performs the balanced scheduling corresponding to the minimum standard deviation, that is, the balanced scheduling for obtaining the minimum standard deviation is to which one or which virtual machines are scheduled to which server or servers, and the balanced scheduling is performed. .

It should be noted that, because distributed resource scheduling is performed for the same type of service virtual machine in each server, distributed resource scheduling of each type of service virtual machine in each server may be separately performed, if resources of a certain type of service virtual machine The distributed resource scheduling is performed using equalization.

It can be seen that a distributed resource scheduling apparatus according to an embodiment of the present invention can ensure the service quality of each service virtual machine in each server by performing distributed resource scheduling according to the type of the service virtual machine in each server in the distributed cluster system. .

As an implementation manner, the first execution unit 17 may be further configured to: after performing the next balanced scheduling, the second standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the current balance scheduling And stopping, according to the second standard deviation of the resource usage rate of the same type of service virtual machine in each server, or ending the next balanced scheduling, if the cumulative number of the balanced scheduling exceeds the first set threshold, stopping executing the servers The acquisition of the second standard deviation of the resource usage rate of the same type of service virtual machine and the next balanced scheduling.

Recursive scheduling can be used to make the scheduling efficiency the highest, and the recursive exit condition is set in the recursive scheduling, that is, if the same type of service virtual machine in each server is used after the next balanced scheduling The second standard deviation of the resource usage rate is greater than or equal to the second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling, or the next balancing scheduling is performed, and the balanced scheduling is performed. When the accumulated number of times exceeds the first set threshold, the first execution unit 17 stops performing the acquisition of the second standard deviation of the resource usage rate of the same type of service virtual machine in each server and the next balanced scheduling. This helps to stop the above acquisition steps and balance scheduling in time, obtain the minimum standard deviation, and perform the balanced scheduling corresponding to the minimum standard deviation.

FIG. 6 is a schematic structural diagram of another distributed resource scheduling apparatus according to an embodiment of the present invention. The device 2000 includes:

The fifth obtaining unit 21 is configured to obtain, according to a proportion of resources of each type of service virtual machines in each server in the distributed cluster system, and a resource usage rate of each type of service virtual machine in each server, Resource usage of each server.

In a distributed cluster system, there are one or more types of service virtual machines in each server. For example, there are desktop cloud virtual machines and compiled cloud virtual machines. DRS allocates certain operations, storage, and input/output to each server in the cluster. Resources, each server allocates the resources it obtains to its internal types of business virtual machines in a certain proportion. Ensure that the total amount and proportion of resources of different types of service virtual machines in each server remain stable, and the service quality of various service virtual machines in each server can be guaranteed.

For example, there are three servers in the cluster. There are two desktop cloud virtual machines and two virtual cloud virtual machines in the server 1. There are three desktop cloud virtual machines, two virtual cloud virtual machines, and a desktop cloud in the server 3. One virtual machine and two virtual machines are compiled. The DRS allocates certain CPU, memory, and I/O resources to the servers 1, 2, and 3 in the cluster. Each server allocates a certain CPU to each internal virtual machine. For example, the memory resource and the I/O resource are allocated to the server 1 by the CPU resource allocation. The DRS allocates the CPU resource of the number A to the server 1, the CPU resource of the quantity B to the server 2, and the CPU resource of the number C to the server 3. 1 Assign the CPU resources of A1, A2, A3, and A4 to the two desktop cloud virtual machines and the two compiled cloud virtual machines respectively. The resource utilization rates of the two desktop cloud virtual machines in server 1 are 30% and 40 respectively. %, the resource usage rate of the two compiled cloud virtual machines in the server 1 is 40% and 50%, respectively, and the resource utilization rate of the CPU of the server 1 is obtained (30%*A1+40%*A2+). 40%*A3+50%A4)/(A1+A2+A3+A4), and then calculate the memory and I/O resource usage of each type of virtual machine in server 1 in the same way, and then server 1 The CPU, memory, and I/O resource usage are weighted to obtain the resource usage of the server 1, and the calculations of the servers 2 and 3 are analogous.

The sixth obtaining unit 22 is configured to acquire, according to the resource usage rate of each server, a third standard deviation of the resource usage rate of the distributed cluster system by using a predetermined acquisition manner, where the obtaining step is: according to the foregoing The resource usage rate of the server acquires the average resource usage rate of the distributed cluster system, and acquires the resources of the distributed cluster system according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system. The third standard deviation of usage.

The difference from the foregoing embodiment is that, for all kinds of service virtual machines in each server, the resource usage rate of each server and the average resource usage rate of the entire distributed cluster system are obtained in the same manner as the foregoing embodiment, and then The sixth obtaining unit 22 obtains the standard deviation of the resource usage rate of the distributed cluster system according to the formula (1).

a second scheduling unit 23, configured to: when the third standard deviation of resource usage of the distributed cluster system is greater than or equal to a scheduling threshold of resource usage of the distributed cluster system, The business virtual machine is balancedly dispatched to other servers of the distributed cluster system.

Comparing the standard deviation of the resource usage rate of the obtained distributed cluster system with the scheduling threshold of the resource usage rate of the distributed cluster system, if the standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the distributed cluster The scheduling threshold of the resource usage rate of the system, the second scheduling unit 23 triggers the balancing scheduling. The object of balanced scheduling can be any business virtual machine in each server.

The seventh obtaining unit 24 is configured to obtain resource usage rates of servers in the distributed cluster system after the balanced scheduling.

The eighth obtaining unit 25 is configured to acquire, according to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, the fourth resource usage rate of the distributed cluster system after the balanced scheduling by using the predetermined acquiring manner Standard deviation.

a second comparison unit 26, configured to compare the fourth standard deviation acquired after the balance scheduling at least once;

The second executing unit 27 is configured to perform the balance scheduling corresponding to the minimum of the fourth standard deviation.

The functions of the seventh obtaining unit 24, the eighth obtaining unit 25, the second comparing unit 26, and the second executing unit 27 are respectively the third obtaining unit 14, the fourth obtaining unit 15, the first comparing unit 16, and the third embodiment of the foregoing embodiment. The function of an execution unit 17 is similar, and is not described here again. The difference is that for each type of service virtual machine in each server, the standard deviation of the resource usage rate of the distributed cluster system is obtained.

It can be seen that the distributed resource scheduling apparatus according to the embodiment of the present invention can ensure the service of each service virtual machine in each server by performing distributed resource scheduling according to the proportion of the resources of the servers in which the various service virtual machines occupy the server. quality.

As a possible implementation manner, the second execution unit 27 is further configured to: after the next balanced scheduling, the fourth standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the distributed after the current balancing scheduling The fourth standard deviation of the resource usage rate of the cluster system, or the next balanced scheduling, the cumulative number of times of the balanced scheduling exceeds a first set threshold, or the service virtual machine is balancedly dispatched from any first server to After any second server, the total amount of the various service virtual machines in any one of the first servers or any of the second servers is greater than a second set threshold, and/or any of the first servers Or the resource usage rate of the distributed cluster system after the balancing scheduling is stopped after the change of the resources of the any one of the first server in the second server is greater than the third set threshold. Acquisition and next balanced scheduling.

Recursive scheduling can be used to make the scheduling efficiency the highest, and the recursive exit condition is set in the recursive scheduling. That is, after the next balanced scheduling, the fourth standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the current balancing scheduling. The fourth standard deviation of the resource usage rate of the distributed cluster system, or the next balanced scheduling, the cumulative number of times of the balanced scheduling exceeds a first set threshold, or the service virtual machine is from any first After the server balances the scheduling to any of the second servers, the total amount of the various service virtual machines in any one of the first servers or any of the second servers is greater than a second set threshold, and/or the A variety of service virtual machines in a first server or any of the second servers account for a large change in resources of any of the first servers After the third setting threshold, the second executing unit 27 stops acquiring the resource usage rate of the distributed cluster system and the next balanced scheduling after the balancing scheduling. This helps to stop the above acquisition steps and balance scheduling in time, obtain the minimum standard deviation, and perform the balanced scheduling corresponding to the minimum standard deviation.

FIG. 7 is a schematic structural diagram of a distributed resource scheduling device according to an embodiment of the present invention. The device 3000 of the embodiment includes a processor 31, a memory 32, an input device 33, an output device 34, and a bus system 35. :

The processor 31 controls the operation of the device 3000, which may also be referred to as a Central Processing Unit (CPU). Processor 31 may be an integrated circuit chip with signal processing capabilities. The processor 31 can also be a general-purpose processor, a digital signal processing (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or the like. Programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general purpose processor may be a microprocessor or the processor or any conventional processor or the like.

Memory 32 can include read only memory and random access memory and provides instructions and data to processor 31. A portion of memory 32 may also include non-volatile random access memory (NVRAM).

The various components of device 3000 are coupled together by a bus system 35, which may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The bus may be one or more physical lines, and when it is a plurality of physical lines, it may be divided into an address bus, a data bus, a control bus, and the like. In some other embodiments of the present invention, the processor 31, the memory 32, and the input device 33 and the output device 34 may also be directly connected through a communication line.

The input device 33 can be implemented as a mouse, a keyboard, a microphone, etc., and the output device 34 can be embodied as a display, an audio device, and a video device. Of course, the input device 33 and the output device 34 can also implement their functions through an input and output device, such as being made touchable. screen.

The processor 31 reads the computer program in the memory 32 to perform the following steps:

Obtaining the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system;

And obtaining, according to the resource usage rate of the service virtual machine of the same type in each server, a first standard deviation of the resource usage rate of the same type of service virtual machine in each server by using a predetermined obtaining step, where the obtaining step is: Acquiring an average resource usage rate of the same type of service virtual machine in each server according to the resource usage rate of the same type of service virtual machine in each server, and according to resource usage of the same type of service virtual machine in each server Rate and the average resource usage rate, obtaining a first standard deviation of resource usage rates of the same type of service virtual machine in each server;

And when the first standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, the distributed cluster is The same type of service virtual machine of any server in the system is balancedly dispatched to other servers of the distributed cluster system;

Obtaining a resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling;

And obtaining the resource usage rate of the same type of service virtual machine in each server by using the predetermined obtaining step according to the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balance scheduling Second standard deviation;

Comparing the second standard deviation acquired after the balanced scheduling at least once, performing the minimum balanced scheduling corresponding to the second standard deviation.

As a possible implementation manner, the processor 31 performs the minimum standard deviation of the second standard deviation corresponding to the second standard deviation obtained after performing the balancing scheduling at least once. , also perform the following steps:

The second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the next balanced scheduling is greater than or equal to the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling The second standard deviation, or the next balance scheduling, if the cumulative number of the balanced scheduling exceeds the first set threshold, the execution of the obtaining step is stopped. The next balance is scheduled.

The computer program included in the processor 31 provided by the embodiment of the present invention may also be implemented as a first acquiring unit, a second acquiring unit, a first scheduling unit, a third acquiring unit, a fourth acquiring unit, a first comparing unit, and the first Executing units, the functions implemented by these units may be referred to the foregoing embodiments, and are not described herein again.

It can be seen that the distributed resource scheduling device according to the embodiment of the present invention can ensure the service quality of each service virtual machine in each server by performing distributed resource scheduling according to the type of the service virtual machine in each server in the distributed cluster system. .

FIG. 8 is a schematic structural diagram of another distributed resource scheduling device according to an embodiment of the present invention. The device 4000 of the embodiment includes a processor 41, a memory 42, an input device 43, an output device 44, and a bus system 45. among them:

The processor 41 controls the operation of the device 4000, which may also be referred to as a Central Processing Unit (CPU). Processor 41 may be an integrated circuit chip with signal processing capabilities. The processor 41 can also be a general-purpose processor, a digital signal processing (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or the like. Programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general purpose processor may be a microprocessor or the processor or any conventional processor or the like.

Memory 42 may include read only memory and random access memory and provides instructions and data to processor 41. A portion of the memory 42 may also include non-volatile random access memory (NVRAM).

The various components of device 4000 are coupled together by a bus system 45, which may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The bus may be one or more physical lines, and when it is a plurality of physical lines, it may be divided into an address bus, a data bus, a control bus, and the like. In some other embodiments of the present invention, the processor 41, the memory 42 and the input The incoming device 43 and the output device 44 can also be directly connected via a communication line.

The input device 43 can be implemented as a mouse, a keyboard, a microphone, etc., and the output device 44 can be embodied as a display, an audio device, and a video device. Of course, the input device 43 and the output device 44 can also implement their functions through an input and output device, such as a touchable screen.

The processor 41 reads the computer program in the memory 42 to perform the following steps:

Obtaining a resource usage rate of each server according to a proportion of resources of each server in each server in the distributed cluster system and a resource usage rate of each type of service virtual machine in each server;

Acquiring, according to the resource usage rate of each server, a first standard deviation of the resource usage rate of the distributed cluster system by using a predetermined obtaining step, where the obtaining step is: acquiring the resource usage rate according to the resource usage of each server The average resource usage of the distributed cluster system, and the first standard deviation of the resource usage rate of the distributed cluster system is obtained according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system;

When the first standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the scheduling threshold of the resource usage rate of the distributed cluster system, balancing any service virtual machines in each server to the In other servers of the distributed cluster system;

Obtaining the resource usage rate of each server in the distributed cluster system after the balanced scheduling;

Obtaining, according to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, obtaining the second standard deviation of the resource usage rate of the distributed cluster system after the balanced scheduling by using the predetermined obtaining step;

Comparing the second standard deviation acquired after the balanced scheduling at least once, performing the minimum balanced scheduling corresponding to the second standard deviation.

As a possible implementation manner, before the step of comparing the second standard deviation acquired after the balance scheduling is performed at least once, the processor 41 performs the step of balancing the balance corresponding to the second standard deviation. Also perform the following steps:

If the second standard deviation of the resource usage rate of the distributed cluster system after the next balanced scheduling is greater than or equal to the second standard deviation of the resource usage rate of the distributed cluster system after the current balancing scheduling, or the next time Balanced scheduling, the cumulative number of times the balanced scheduling is performed exceeds After setting the threshold, or balancing the service virtual machine from any first server to any second server, the service virtual machine of any one of the first server or any of the second servers The change of the total amount is greater than the second set threshold, and/or the change of the resources of the first server or the any of the second servers in the service virtual machine of any one of the first servers is greater than When the threshold is set third, the obtaining step and the next balanced scheduling are stopped.

The computer program included in the processor 41 provided by the embodiment of the present invention may also be implemented as a fifth obtaining unit, a sixth obtaining unit, a second scheduling unit, a seventh obtaining unit, an eighth obtaining unit, a second comparing unit, and a second Executing units, the functions implemented by these units may be referred to the foregoing embodiments, and are not described herein again.

It can be seen that the distributed resource scheduling device according to the embodiment of the present invention can ensure the service of each service virtual machine in each server by performing distributed resource scheduling according to the proportion of the resources of the servers in which the various service virtual machines occupy the server. quality.

It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should understand that the present invention is not limited by the described action sequence. Because certain steps may be performed in other sequences or concurrently in accordance with the present invention. In addition, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

In the above embodiments, the descriptions of the various embodiments are different, and the details that are not detailed in a certain embodiment can be referred to the related descriptions of other embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented in hardware, firmware implementation, or a combination thereof. When implemented in software, the functions described above may be stored in or transmitted as one or more instructions or code on a computer readable medium. Computer readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one location to another. A storage medium may be any available media that can be accessed by a computer. For example, but not limited to, the computer readable medium may include a random access memory (RAM), a read-only memory (ROM), and an electrically erasable programmable read-only memory (Electrically Erasable Programmable). Read-Only Memory, EEPROM, Compact Disc Read-Only Memory (CD-ROM) or other Optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also. Any connection may suitably be a computer readable medium. For example, if the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, Then coaxial cable, fiber optic cable, twisted pair, DSL or wireless technologies such as infrared, wireless and microwave are included in the fixing of the associated medium. As used in the present invention, a disk and a disc include a compact disc (CD), a laser disc, a compact disc, a digital versatile disc (DVD), a floppy disk, and a Blu-ray disc, wherein the disc is usually magnetically copied, and the disc is The laser is used to optically replicate the data. Combinations of the above should also be included within the scope of the computer readable media.

In summary, the above description is only a preferred embodiment of the technical solution of the present invention, and is not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and scope of the present invention are intended to be included within the scope of the present invention.

Claims (8)

A distributed resource scheduling method, comprising: Obtaining the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system; And obtaining, according to the resource usage rate of the service virtual machine of the same type in each server, a first standard deviation of the resource usage rate of the same type of service virtual machine in each server by using a predetermined obtaining step, where the obtaining step is: Acquiring an average resource usage rate of the same type of service virtual machine in each server according to the resource usage rate of the same type of service virtual machine in each server, and according to resource usage of the same type of service virtual machine in each server Rate and the average resource usage rate, obtaining a first standard deviation of resource usage rates of the same type of service virtual machine in each server; And when the first standard deviation of the resource usage rate of the same type of service virtual machine in each server is greater than or equal to the scheduling threshold of the resource usage rate of the same type of service virtual machine in each server, the distributed cluster is The same type of service virtual machine of any server in the system is balancedly dispatched to other servers of the distributed cluster system; Obtaining a resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling; And obtaining the resource usage rate of the same type of service virtual machine in each server by using the predetermined obtaining step according to the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system after the balance scheduling Second standard deviation; Comparing the second standard deviation acquired after the balanced scheduling at least once, performing the minimum balanced scheduling corresponding to the second standard deviation. The method according to claim 1, wherein the comparing the second standard deviation acquired after the balanced scheduling at least once, before performing the minimum balanced scheduling corresponding to the second standard deviation, further include: If the second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the next balanced scheduling is greater than or equal to that in the servers after performing the current balancing scheduling The second standard deviation of the resource usage rate of the same type of service virtual machine, or the next balance scheduling, if the cumulative number of the balanced scheduling exceeds the first set threshold, the execution of the obtaining step and the next balanced scheduling are stopped. . A distributed resource scheduling method, comprising: Obtaining a resource usage rate of each server according to a proportion of resources of each server in each server in the distributed cluster system and a resource usage rate of each type of service virtual machine in each server; Acquiring, according to the resource usage rate of each server, a third standard deviation of the resource usage rate of the distributed cluster system by using a predetermined obtaining step, where the obtaining step is: acquiring the resource according to the resource usage rate of each server The average resource usage of the distributed cluster system, and the third standard deviation of the resource usage rate of the distributed cluster system is obtained according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system; When the third standard deviation of the resource usage rate of the distributed cluster system is greater than or equal to the scheduling threshold of the resource usage rate of the distributed cluster system, balancing any service virtual machine in each server to the In other servers of the distributed cluster system; Obtaining the resource usage rate of each server in the distributed cluster system after the balanced scheduling; And obtaining, according to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, the fourth standard deviation of the resource usage rate of the distributed cluster system after the balanced scheduling by using the predetermined obtaining step; Comparing the fourth standard deviation acquired after the balanced scheduling at least once, performing the minimum balanced scheduling corresponding to the fourth standard deviation. The method according to claim 3, wherein the comparing the fourth standard deviation acquired after the balanced scheduling at least once, before performing the minimum balanced scheduling corresponding to the fourth standard deviation, include: If the fourth standard deviation of the resource usage rate of the distributed cluster system after the next balanced scheduling is greater than or equal to the fourth standard deviation of the resource usage rate of the distributed cluster system after the current balancing scheduling, or the next time Balanced scheduling, the cumulative number of times of performing the balanced scheduling exceeds a first set threshold, or the business virtual machine is balancedly dispatched from any first server to any of the first After the second server, the total amount of the various service virtual machines in any one of the first servers or any of the second servers is greater than a second set threshold, and/or the any first server or the If the change of the resources of the first service server in any of the second servers is greater than the third set threshold, the obtaining step and the next balanced scheduling are stopped. A distributed resource scheduling device, comprising: a first acquiring unit, configured to acquire resource usage rates of the same type of service virtual machines in each server in the distributed cluster system; a second acquiring unit, configured to acquire, according to a resource usage rate of the same type of service virtual machine in each server, a first standard deviation of resource usage rates of the same type of service virtual machine in each server by using a predetermined acquisition manner Obtaining, according to the resource usage rate of the same type of service virtual machine in each server, obtaining an average resource usage rate of the same type of service virtual machine in each server, and according to the same in each server The resource usage rate of the type service virtual machine and the average resource usage rate, and obtaining a first standard deviation of resource usage rates of the same type of service virtual machine in each server; a first scheduling unit, configured to: when a first standard deviation of resource usage rates of the same type of service virtual machines in the servers is greater than or equal to a scheduling threshold of resource usage rates of the same type of service virtual machines in each server And balancing the same type of service virtual machines of any one of the servers in the distributed cluster system to other servers of the distributed cluster system; a third acquiring unit, configured to obtain resource usage rates of the same type of service virtual machine in each server in the distributed cluster system after the balanced scheduling; a fourth acquiring unit, configured to acquire, according to the resource usage rate of the same type of service virtual machine in each server in the distributed cluster system, the same type in each server The second standard deviation of the resource usage of the business virtual machine; a first comparing unit, configured to compare the second standard deviation acquired after the balancing scheduling at least once; a first execution unit, configured to perform the balance scheduling corresponding to the minimum of the second standard deviation. The apparatus of claim 5, wherein the first execution unit is further configured to: If the next balancing operation is performed, the resources of the same type of service virtual machine in each server are used. The second standard deviation of the source usage rate is greater than or equal to the second standard deviation of the resource usage rate of the same type of service virtual machine in each server after the current balancing scheduling, or the next balancing scheduling is performed, and the balanced scheduling is performed. When the accumulated number of times exceeds the first set threshold, the acquisition of the second standard deviation of the resource usage rate of the same type of service virtual machine in each server and the next balanced scheduling are stopped. A distributed resource scheduling device, comprising: a fifth obtaining unit, configured to acquire, according to a proportion of resources of each type of service virtual machines in each server in the distributed cluster system, and a resource usage rate of each type of service virtual machine in each server, Server resource usage rate; a sixth obtaining unit, configured to acquire, according to the resource usage rate of each server, a third standard deviation of the resource usage rate of the distributed cluster system by using a predetermined acquisition manner, where the obtaining manner is: according to each server The resource usage rate obtains the average resource usage rate of the distributed cluster system, and acquires resource usage of the distributed cluster system according to the resource usage rate of each server and the average resource usage rate of the distributed cluster system. The third standard deviation of the rate; a second scheduling unit, configured to: when the third standard deviation of resource usage of the distributed cluster system is greater than or equal to a scheduling threshold of resource usage of the distributed cluster system, any service in each server Virtual machine balancing is dispatched to other servers of the distributed cluster system; a seventh acquiring unit, configured to obtain resource usage rates of servers in the distributed cluster system after the balanced scheduling; An eighth obtaining unit, configured to acquire, according to the resource usage rate of each server in the distributed cluster system after the balanced scheduling, the fourth standard of resource utilization rate of the distributed cluster system after the balanced scheduling by using the predetermined acquiring manner difference; a second comparing unit, configured to compare the fourth standard deviation acquired after the balanced scheduling at least once; a second execution unit, configured to perform the balance scheduling corresponding to the minimum of the fourth standard deviation. The device according to claim 7, wherein the second execution unit is further configured to: The fourth standard of resource utilization rate of the distributed cluster system after the next balanced scheduling The quasi-differential is greater than or equal to the fourth standard deviation of the resource usage rate of the distributed cluster system after the current balancing scheduling, or the next balancing scheduling, and the cumulative number of the balancing scheduling exceeds the first set threshold, or After the service virtual machine is balancedly dispatched from any of the first servers to any of the second servers, the total amount of the various service virtual machines in any of the first servers or any of the second servers is greater than the second Setting a threshold, and/or the change of resources of any one of the first server or any of the second servers in the any one of the first servers is greater than a third set threshold, then stopping After the balanced scheduling is performed, the resource usage rate of the distributed cluster system is acquired and the next balanced scheduling is performed.

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