Automatic workload transfer to an on-demand center

• US 9,413,687 B2
• Filed: 03/16/2006
• Issued: 08/09/2016
• Est. Priority Date: 03/16/2005
• Status: Active Grant

• Current Assignee: III Holdings 12, LLC (Intellectual Ventures LLC)
• Original Assignee: Adaptive Computing Enterprises, Inc. (Ala Services LLC)
• Inventors: Jackson, David B.
• Primary Examiner(s): Eskandarnia, Arvin
• Assistant Examiner(s): DESAI, MARGISHI V
• Application Number:
  US11/276,853
• Publication Number:
  US 20060224741A1
• Time in Patent Office: 3,799 Days
• Field of Search: 709/226, 709/224, 709/205, 705/52
• US Class Current: 1/1
• CPC Class Codes: G06F 11/2038 with a single idle spare processing component
• CPC Class Codes: G06F 15/173 using an interconnection network, e.g. matrix, shuffle, pyramid, star, snowflake
• CPC Class Codes: G06F 2209/5014 Reservation
• CPC Class Codes: G06F 2209/509 Offload
• CPC Class Codes: G06F 9/5027 the resource being a machine, e.g. CPUs, Servers, Terminals
• CPC Class Codes: G06F 9/5061 Partitioning or combining of resources
• CPC Class Codes: G06F 9/5072 Grid computing
• 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: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G08C 17/00 Arrangements for transmitting signals characterised by the use of a wireless electrical link
• CPC Class Codes: H04L 47/70 Admission control; Resource allocation
• CPC Class Codes: H04L 47/80 Actions related to the user profile or the type of traffic
• CPC Class Codes: H04L 47/83 based on usage prediction
• CPC Class Codes: H04L 67/10 in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network

Abstract

Disclosed is an on-demand computing environment. The method embodiment relates to a method of managing resources between a local compute environment and an on-demand environment. The method includes detecting an event in a local compute environment and based on the detected event, automatically establishing communication with an on-demand compute environment, provisioning resources within the on-demand compute environment and transferring workload from the local compute environment transparently to the on-demand compute environment.

Claims

1. A method of managing resources, the method comprising:

detecting an event in a local compute environment, the local compute environment comprising a plurality of resources configured to process workload, to yield a detected event;

based on the detected event, receiving a request for resources in an on-demand compute environment, the resources comprising at least one of a server, memory, network bandwidth, a processor, and a virtual resource, wherein a specification of the resources associated with the request is one of fully explicit, partially explicit, and fully implicit based on workload;

establishing a communication between the local compute environment and the on-demand compute environment having a plurality of resources available to process workload under common management separate from the local compute environment;

based on the communication, establishing, at a first time and associated with the request for resources, a reservation of the resources for use at a second time later than the first time within the on-demand compute environment to yield reserved resources; and

transferring workload, submitted for processing in the local compute environment, transparently to the on-demand compute environment to yield transferred workload, wherein the transferred workload consumes the reserved resources in the on-demand compute environment at the second time.

2. The method of claim 1, wherein at least one of:

(1) local information associated with the local compute environment is imported to the on-demand compute environment and (2) on-demand information associated with the on-demand compute environment is communicated to the local compute environment.

3. The method of claim 2, wherein workload information is communicated from the local compute environment to the on-demand compute environment.

4. The method of claim 2, wherein if on-demand information is communicated to the local compute environment, the on-demand information relates to an availability of resources in the on-demand compute environment for use by the local compute environment.

5. The method of claim 1, further comprising:

transparently handling data management between a slave module in the on-demand compute environment and a client module in the local compute environment.

6. The method of claim 5, wherein transparently handling data management further comprises handling the data management such that the establishing of the reservation of resources within the on-demand compute environment and transferring the workload from the local compute environment is performed unknown to a user who submitted the workload to the local compute environment.

7. The method of claim 1, wherein the event is related to at least one:

of a resource threshold, a service threshold, a policy threshold and an event outside the local compute environment.

8. The method of claim 1, wherein the event further comprises a failure of at least one a compute node, a network device, a storage device, a license, a service, an information service, a web service, a database service and a security service.

9. The method of claim 1, wherein establishing communication with the on-demand compute environment further comprises importing from the local compute environment at least one of class information, configuration policy information and other information to the on-demand compute environment.

10. The method of claim 1, wherein establishing communication with the on-demand compute environment occurs automatically.

11. The method of claim 1, wherein the event is based on one of all workload associated with the local compute environment or a subset of workload associated with the local compute environment.

12. The method of claim 1, wherein establishing a reservation of compute resources within the on-demand compute environment is based on at least one of implicit and explicit requirements.

17. The method of claim 1, further comprising provisioning the reserved resources.

13. A method of managing a relationship between a local compute environment and an on-demand compute environment, the method comprising:

detecting a resource need event in the local compute environment under common management separate from the on-demand compute environment, the local compute environment comprising a plurality of resources configured to process workload, to yield a detected resource need event;

based on the detected resource need event, negotiating and establishing a relationship between the local compute environment and the on-demand compute environment;

receiving a request for resources in the on-demand compute environment, the resources comprising at least one of a server, memory, network bandwidth, a processor, and a virtual resource, wherein a specification of the resources associated with the request is one of fully explicit, partially explicit, and fully implicit based on workload;

establishing, at a first time, a reservation of resources for consumption at a second time later than the first time and within the on-demand compute environment to yield reserved resources; and

transferring workload, submitted for processing on the local compute environment, transparently to the on-demand compute environment to yield transferred workload, wherein the transferred workload consumes the reserved resources in the on-demand compute environment at the second time.

14. The method of claim 13, wherein the resource need event is one of a current resource need and a predicted resource need.

18. The method of claim 13, further comprising provisioning the reserved resources.

15. A system for managing resources between a local compute environment and an on-demand compute environment, the system comprising:

a processor; and

a computer readable storage medium storing instructions which, when executed by the processor, cause the processor to perform operations comprising;

detecting an event in the local compute environment having multiple resources available to process workload under common management and separate from the on-demand compute environment, the local compute environment configured to process workload;

based on the event, receiving a request for resources in an on-demand compute environment, the resources comprising at least one of a server, memory, network bandwidth, a processor, and a virtual resource, wherein a specification of the resources associated with the request is one of fully explicit, partially explicit, and fully implicit based on workload;

establishing a communication between the local compute environment and the on-demand compute environment;

reserving resources, at a first time, within the on-demand compute environment to yield reserved resources for use at a second time later than the first time; and

transferring workload, submitted for processing on the local compute environment, transparently to the on-demand compute environment to yield transferred workload, wherein the transferred workload consumes the reserved resources in the on-demand compute environment at the second time.

19. The system of claim 15, further comprising a fifth module configured to control the processor to provision the reserved resources.

16. A non-transitory computer readable storage medium storing instruction for controlling a computing device to manage resources in a local compute environment and an on-demand compute environment, the instructions causing the computing device to perform operations comprising:

detecting an event in a local compute environment under common management separate from the on-demand compute environment, the local compute environment having a plurality of resources configured to process workload;

based on the event, receiving a request for resources in the on-demand compute environment, the resources comprising at least one of a server, memory, network bandwidth, a processor, and a virtual resource, wherein a specification of the resources associated with the request is one of fully explicit, partially explicit, and fully implicit based on workload;

establishing communication between the local compute environment and the on-demand compute environment;

reserving, at a first time, resources within the on-demand compute environment to yield reserved resources for use at a second time which is later than the first time; and

transferring, workload submitted for processing on the local compute environment, transparently to the on-demand compute environment to yield transferred workload, wherein the transferred workload consumes the reserved resources in the on-demand compute environment at the second time.

20. The non-transitory computer-readable storage medium of claim 16, the instructions further comprising provisioning the reserved resources.