Adaptive power management of a cluster of host computers using predicted data

• US 10,460,362 B2
• Filed: 08/07/2018
• Issued: 10/29/2019
• Est. Priority Date: 08/24/2013
• Status: Active Grant

• Current Assignee: Vmware LLC (Broadcom, Inc.)
• Original Assignee: VMware, Inc. (Broadcom, Inc.)
• Inventors: Parikh, Aashish
• Primary Examiner(s): Johnson, Terrell S
• Application Number:
  US16/056,913
• Publication Number:
  US 20180374129A1
• Time in Patent Office: 448 Days
• CPC Class Codes: G06F 1/26 Power supply means, e.g. regulation thereof for memories G11C
• CPC Class Codes: G06F 1/3209 Monitoring remote activity, e.g. over telephone lines or network connections
• CPC Class Codes: G06F 11/3062 where the monitored property is the power consumption power management in a computing system G06F1/3203
• CPC Class Codes: G06F 9/5044 considering hardware capabilities
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: G06F 9/5077 Logical partitioning of resources; Management or configuration of virtualized resources specific details on emulation or internal functioning of virtual machines G06F9/455
• CPC Class Codes: G06F 9/5094 where the allocation takes into account power or heat criteria power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H04L 67/01 Protocols
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/1097 for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management

Abstract

Aspects of performing power management operations in a distributed computer system are described. In some aspects, predicted demand data is generated for clients executed in a cluster of host computers. The predicted demand data is based on observed resource demands of the clients. A power management setting for a time period is determined. The power management setting is based on the predicted demand data. A host computer is caused to power-down or power-up in order to apply the power management setting.

Claims

1. A method performed by a computing device, the method comprising:

generating predicted demand data for clients executed in a cluster of host computers, the predicted demand data based on observed resource demands of the clients;

determining a host utilization setting to apply for a particular time period, the host utilization setting based on the predicted demand data; and

causing, prior to the particular time period, a gradual adjustment from an initial host utilization setting to the host utilization setting, the gradual adjustment comprising at least one intermediate host utilization setting, wherein a host computer of the cluster performs one of;

a power-down or a power-up based on the gradual adjustment.

2. The method of claim 1, further comprising:

migrating a particular client from a first host computer of the cluster to a second host computer of the cluster, the particular client being migrated to apply the host utilization setting, wherein the host computer is one of;

the first host computer or the second host computer.

3. The method of claim 2, wherein the predicted demand data comprises a near-zero demand value for the particular client.

4. The method of claim 1, wherein the particular time period is associated with a portion of a twenty-four hour cycle, and the host utilization setting is determined based on the observed resource demands during the portion of the twenty-four hour cycle.

5. The method of claim 1, wherein the host utilization setting comprises a percentage of the host computers to utilize during the particular time period.

6. The method of claim 1, further comprising:

determining an intermediate host utilization setting to apply for an interval before the host utilization setting is applied; and

applying the intermediate host utilization setting to cause the gradual change from the initial host utilization setting to the host utilization setting.

7. The method of claim 1, wherein the host utilization setting specifies a duration that the host computer is required to be powered-on before the power-down.

8. A system comprising:

a computing device comprising a processor; and

a storage device comprising executable instructions which, when executed by the processor, cause the computing device to at least;

generate predicted demand data for clients executed in a cluster of host computers, the predicted demand data based on observed resource demands of the clients;

determine a host utilization setting for a particular time period, the host utilization setting based on the predicted demand data; and

cause, prior to the particular time period, a gradual adjustment from an initial host utilization setting to the host utilization setting, the gradual adjustment comprising at least one intermediate host utilization setting, wherein a host computer of the cluster performs one of;

a power-down or a power-up based on the gradual adjustment.

9. The system of claim 8, wherein the executable instructions, when executed by the processor, further cause the computing device to at least:

migrate a particular client from a first host computer of the cluster to a second host computer of the cluster, the particular client being migrated to apply the host utilization setting, wherein the host computer is one of;

the first host computer or the second host computer.

10. The system of claim 9, wherein the predicted demand data comprises a near-zero demand value for the particular client.

11. The system of claim 8, wherein the particular time period is associated with a portion of a twenty-four hour cycle, and the host utilization setting is determined based on the observed resource demands during the portion of the twenty-four hour cycle.

12. The system of claim 8, wherein the host utilization setting comprises a percentage of the host computers to utilize during the particular time period.

13. The system of claim 8, wherein the executable instructions, when executed by the processor, further cause the computing device to at least:

determine an intermediate host utilization setting to apply for an interval before the host utilization setting is applied; and

apply the intermediate host utilization setting to gradually change from the initial host utilization setting to the host utilization setting.

14. The system of claim 8, wherein the host utilization setting specifies a duration that the host computer is required to be powered-on before the power-down.

15. A non-transitory computer readable storage medium embodying executable instructions which, when executed by a processor, cause a computing device to at least:

generate predicted demand data for clients executed in a cluster of host computers, the predicted demand data based on observed resource demands of the clients;

determine a host utilization setting for a particular time period, the host utilization setting based on the predicted demand data; and

cause, prior to the particular time period, a gradual adjustment from an initial host utilization setting to the host utilization setting, the gradual adjustment comprising at least one intermediate host utilization setting, wherein a host computer of the cluster performs one of;

a power-down or a power-up based on the gradual adjustment.

16. The non-transitory computer readable storage medium of claim 15, wherein the executable instructions, when executed by the processor, further cause the computing device to at least:

migrate a particular client from a first host computer of the cluster to a second host computer of the cluster, the particular client being migrated to apply the host utilization setting, wherein the host computer is one of;

the first host computer or the second host computer.

17. The non-transitory computer readable storage medium of claim 16, wherein the predicted demand data comprises a near-zero demand value for the particular client.

18. The non-transitory computer readable storage medium of claim 15, wherein the particular time period is associated with a portion of a twenty-four hour cycle, and the host utilization setting is determined based on the observed resource demands during the portion of the twenty-four hour cycle.

19. The non-transitory computer readable storage medium of claim 15, wherein the host utilization setting comprises a percentage of the host computers to utilize during the particular time period.

20. The non-transitory computer readable storage medium of claim 15, wherein the executable instructions, when executed by the processor, further cause the computing device to at least:

determine an intermediate host utilization setting to apply for an interval before the host utilization setting is applied; and

apply the intermediate host utilization setting to gradually change from the initial host utilization setting to the host utilization setting.