ADAPTIVE RESOURCE MANAGEMENT OF A CLUSTER OF HOST COMPUTERS USING PREDICTED DATA

• US 20160021024A1
• Filed: 07/16/2014
• Published: 01/21/2016
• Est. Priority Date: 07/16/2014
• Status: Active Grant

• Current Assignee: Vmware LLC (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Parikh, Aashish
• Granted Patent: US 11,307,884 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 2009/45566 Nested virtual machines
• CPC Class Codes: G06F 2009/4557 Distribution of virtual machine instances; Migration and load balancing
• CPC Class Codes: G06F 2009/45595 Network integration; Enabling network access in virtual machine instances
• CPC Class Codes: G06F 9/45558 Hypervisor-specific management and integration aspects
• CPC Class Codes: G06F 9/50 Allocation of resources, e.g. of the central processing unit [CPU]

Abstract

A resource management system and method for performing resource management operations in a distributed computer system uses predicted resource demands for a specified time in the future to change a resource management option of a resource management analysis algorithm prior to the specified time so that the resource management analysis algorithm can be executed in anticipation of the predicted resource demands at the specified time.

Claims

1. A method for performing resource management operations in a distributed computer system, the method comprising:

analyzing resource demands of clients running in the distributed computer system to produce predicted resource demands for a specified time in the future;

changing a resource management option of a resource management analysis algorithm from a first option setting to a second option setting at a first time prior to the specified time; and

executing the resource management analysis algorithm with the second option setting in anticipation of the predicted resource demands at the specified time.

2. The method of claim 1, wherein the clients running in the distributed computer system are virtual machines and the resource demands are demands of virtualized resources.

3. The method of claim 1, wherein the analyzing the resource demands by the clients includes analyzing at least one of processor and memory demands of the clients running in the distributed computer system.

4. The method of claim 1, wherein the second option setting of the resource management option is more aggressive with respect to load balancing than the first option setting.

5. The method of claim 1, wherein the second option setting of the resource management option is less aggressive with respect to load balancing than the first option setting.

6. The method of claim 1, further comprising:

changing the resource management option of the resource management analysis algorithm from the second option setting to a third option setting at a second time subsequent to the first time and prior to the specified time; and

executing the resource management analysis algorithm with the third option setting.

7. The method of claim 6, wherein the second option setting of the resource management option is less aggressive with respect to load balancing than the first option setting and wherein the third option setting is less aggressive with respect to load balancing than the second option.

8. The method of claim 1, wherein the resource management option of the resource management analysis algorithm is related to an amount of computation that is performed by the resource management analysis algorithm to find a solution for load balancing.

9. The method of claim 1, wherein the resource management option of the resource management analysis algorithm is related to an ability of the resource management analysis algorithm to aggressively perform a load-balance analysis.

10. A computer-readable storage medium containing program instructions for performing resource management operations in a distributed computer system, wherein execution of the program instructions by one or more processors of a computer system causes the one or more processors to perform steps comprising:

analyzing resource demands of clients running in the distributed computer system to produce predicted resource demands for a specified time in the future;

changing a resource management option of a resource management analysis algorithm from a first option setting to a second option setting at a first time prior to the specified time; and

executing the resource management analysis algorithm with the second option setting in anticipation of the predicted resource demands at the specified time.

11. The computer-readable storage medium of claim 10, wherein the clients running in the distributed computer system are virtual machines and the resource demands are demands of virtualized resources.

12. The computer-readable storage medium of claim 10, wherein the analyzing the resource demands by the clients includes analyzing at least one of processor and memory demands of the clients running in the distributed computer system.

13. The computer-readable storage medium of claim 10, wherein the second option setting of the resource management option is more aggressive with respect to load balancing than the first option setting.

14. The computer-readable storage medium of claim 10, wherein the second option setting of the resource management option is less aggressive with respect to load balancing than the first option setting.

15. The computer-readable storage medium of claim 10, further comprising:

changing the resource management option of the resource management analysis algorithm from the second option setting to a third option setting at a second time subsequent to the first time and prior to the specified time; and

executing the resource management analysis algorithm with the third option setting.

16. The computer-readable storage medium of claim 15, wherein the second option setting of the resource management option is less aggressive with respect to load balancing than the first option setting and wherein the third option setting is less aggressive with respect to load balancing than the second option.

17. The computer-readable storage medium of claim 10, wherein the resource management option of the resource management analysis algorithm is related to an amount of computation that is performed by the resource management analysis algorithm to find a solution for load balancing.

18. A resource management system supported by hardware in a distributed computer system comprising:

an analytics engine configured to analyze resource demands of clients running in the distributed computer system to produce predicted resource demands for a specified time in the future;

an option setting unit configured to change a resource management option of a resource management analysis algorithm from a first option setting to a second option setting at a first time prior to the specified time; and

a resource management module configured to execute the resource management analysis algorithm with the second option setting in anticipation of the predicted resource demands at the specified time.

19. The resource management system of claim 18, wherein the clients running in the distributed computer system are virtual machines and the resource demands are demands of virtualized resources.

20. The resource management system of claim 18, wherein the analytics engine is configured to analyze at least one of processor and memory demands of the clients running in the distributed computer system.

21. The resource management system of claim 18, wherein the second option setting of the resource management option is more aggressive with respect to load balancing management than the first option setting.

22. The resource management system of claim 18, wherein the second option setting of the resource management option is less aggressive with respect to load balancing than the first option setting.

23. The resource management system of claim 18, wherein the option setting unit is further configured to change the resource management option of the resource management analysis algorithm from the second option setting to a third option setting at a second time subsequent to the first time and prior to the specified time and wherein the resource management module is configured to execute the resource management analysis algorithm with the third option setting.

24. The resource management system of claim 23, wherein the second option setting of the resource management option is less aggressive with respect to load balancing than the first option setting and wherein the third option setting is less aggressive with respect to load balancing than the second option.