Data center system that accommodates episodic computation

• US 9,886,316 B2
• Filed: 08/20/2014
• Issued: 02/06/2018
• Est. Priority Date: 10/28/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Belady, Christian L., Larus, James R., Reed, Danny A., Borgs, Christian H., Chayes, Jennifer Tour, Lobel, Ilan, Menache, Ishai, Nazerzadeh, Hamid, Jain, Navendu
• Primary Examiner(s): Singh, Gurkanwaljit
• Application Number:
  US14/464,650
• Publication Number:
  US 20140365402A1
• Time in Patent Office: 1,266 Days
• Field of Search: None
• CPC Class Codes: G06F 1/3203 Power management, i.e. event-based initiation of a power-saving mode
• CPC Class Codes: G06F 1/329 by task scheduling
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals
• CPC Class Codes: G06F 9/505 considering the load
• 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 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: H04L 45/00 Routing or path finding of packets in data switching networks routing or path finding in wireless networks H04W40/00
• CPC Class Codes: H04L 67/1004 Server selection for load balancing
• CPC Class Codes: Y02B 70/10 Technologies improving the efficiency by using switched-mode power supplies [SMPS], i.e. efficient power electronics conversion e.g. power factor correction or reduction of losses in power supplies or efficient standby modes
• CPC Class Codes: Y02D 10/00 Energy efficient computing, e.g. low power processors, power management or thermal management
• CPC Class Codes: Y02P 90/82 Energy audits or management systems therefor
• CPC Class Codes: Y02P 90/90 Financial instruments for climate change mitigation, e.g. environmental taxes, subsidies or financing
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
• CPC Class Codes: Y04S 50/12 Billing, invoicing, buying or selling transactions or other related activities, e.g. cost or usage evaluation
• CPC Class Codes: Y04S 50/14 : Marketing, i.e. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards

Abstract

A data center system is described which includes multiple data centers powered by multiple power sources, including any combination of renewable power sources and on-grid utility power sources. The data center system also includes a management system for managing execution of computational tasks by moving data components associated with the computational tasks within the data center system, in lieu of, or in addition to, moving power itself. The movement of data components can involve performing pre-computation or delayed computation on data components within any data center, as well as moving data components between data centers. The management system also includes a price determination module for determining prices for performing the computational tasks based on different pricing models. The data center system also includes a “stripped down” architecture to complement its use in the above-summarized data-centric environment.

Claims

1. A system, comprising:

one or more processing devices; and

a storage device storing computer readable instructions which, when executed by the one or more processing devices, cause the one or more processing devices to;

delay times at which data components associated with computational tasks are to be performed within data centers of a data center system, resulting in delayed data components;

monitor available power types at the data centers, the data centers being located at different locations supplied by different respective power resources; and

move the delayed data components to a new location in the data center system based at least in part on a type of available power at the new location.

2. The system of claim 1, wherein the type of available power at the new location is renewable energy.

3. The system of claim 1, wherein the computer readable instructions further cause the one or more processing devices to move the delayed data components based at least in part on cost of power at the data centers.

4. The system of claim 1, wherein the computer readable instructions further cause the one or more processing devices to delay the times based at least in part on ages of the data centers.

5. A system, comprising:

one or more processing devices; and

a storage device storing computer readable instructions which, when executed by the one or more processing devices, cause the one or more processing devices to;

monitor different power resources available to data centers located at different respective data center locations;

determine power requirements for the data centers to process data components associated with a computational task;

identify an individual data component to move from a first data center to a second data center based at least in part on a first power requirement for the first data center to process the individual data component and first power resources available to the first data center; and

select the second data center based at least in part on a second power requirement for the second data center to process the individual data component and second power resources available to the second data center.

6. The system of claim 5, wherein the computer readable instructions further cause the one or more processing devices to:

determine to move the individual data component based at least in part on a change in the first power resources.

7. The system of claim 5, wherein the computer readable instructions further cause the one or more processing devices to:

select the second data center based at least in part on a type of the second power resources available at the second data center.

8. The system of claim 7, wherein the type is renewable power and the second data center is selected over a third data center that lacks renewable power.

9. The system of claim 5, wherein the second power requirement is lower than the first power requirement.

10. The system of claim 9, wherein equipment at the second data center consumes less power to process the individual data component than other equipment at the first data center.

11. The system of claim 5, wherein the computer readable instructions further cause the one or more processing devices to:

repeatedly determine whether to move other individual data components from the first data center based at least in part on the first power resources available to the first data center.

12. The system of claim 5, wherein the computer readable instructions further cause the one or more processing devices to:

select the second data center based at least in part on a cost of moving the individual data component to the second data center.

13. The system of claim 5, wherein the data centers are part of a data center system, and the computer readable instructions further cause the one or more processing devices to:

determine to move the individual data component from the first data center to the second data center based at least in part on consideration of bandwidth resources of the second data center for communicating within the system.

14. A method, comprising:

monitoring performance of computational tasks at data centers in a data center system, the computational tasks comprising data components;

monitoring different types of power resources available to the data centers at different data center locations;

determining whether to move an individual data component from a first data center at a first data center location to a second data center at a second data center location;

in a first instance, moving the individual data component to the second data center based at least in part on a first type of the power resources available at the first data center location and a second type of the power resources available at the second data center location; and

in a second instance, processing another individual data component at the first data center without moving the another individual data component to another data center based at least in part on predicted power availability at the another data center.

15. The method of claim 14, further comprising:

in the first instance, selecting the second data center based at least in part on a bandwidth cost of moving the individual data component to the second data center.

16. The method of claim 14, further comprising:

in the first instance, selecting the second data center based at least in part on latency-related costs of moving the individual data component to the second data center.

17. The method of claim 16, wherein the individual data component is a delayed computation component and the latency-related costs are associated with storing and retrieving the delayed computation component.

18. The method of claim 16, wherein the latency-related costs include an inventory-related cost of the individual data component becoming out-of-date.

19. The method of claim 14, further comprising:

in the first instance, moving the individual data component to the second data center based at least in part on power requirements of equipment at the first data center versus the second data center.

20. The method of claim 19, wherein the power requirements of the equipment at the first data center are higher than at the second data center.