INTEGRATED PLACEMENT PLANNING FOR HETEROGENOUS STORAGE AREA NETWORK DATA CENTERS

• US 20080295094A1
• Filed: 05/22/2007
• Published: 11/27/2008
• Est. Priority Date: 05/22/2007
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Korupolu, Madhukar R., Bamba, Bhuvan, Singh, Aameek
• Granted Patent: US 8,341,623 B2
• Time in Patent Office: Days
• US Class Current: 718/1
• CPC Class Codes: G06F 9/5066 Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs mappping at compile time, see G06F8/451
• 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: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30
• CPC Class Codes: H04L 67/101 based on network conditions
• CPC Class Codes: H04L 67/1021 based on client or server locations
• CPC Class Codes: H04L 67/1023 based on a hash applied to IP addresses or costs
• 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]

Abstract

A program, method and system are disclosed for planning the placement of a collection of applications in a heterogeneous storage area network data center. The program, method, and system disclosed deal with the coupled placement of virtual machine applications within a resource graph, with each application requiring a certain amount of CPU resources and a certain amount of storage resources from the connected resource node pairs within the resource graph. The resource nodes in the graph provide either storage resources, CPU resources, or both and can have differing degrees of affinity between different node pairs. Various placement algorithms may be used to optimize placement of the applications such as an individual-greedy, pair-greedy or stable marriage algorithm. One placement objective may be to place the programs among nodes of the resource graph without exceeding the storage and CPU capacities at nodes while keeping the total cost over all applications small.

Claims

1. A computer program embodied on a computer readable medium, comprising:

program instructions for receiving a resource graph describing a storage area network (SAN), the resource graph comprising a plurality of connected resource nodes each providing one or more resources where the resources include processing capability and storage capability for virtual machine applications;

program instructions for receiving a collection of applications each requiring a certain amount of CPU resource element and a certain amount of storage resource element; and

program instructions for determining coupled placement of the processing requirement element and the storage requirement element of each of the virtual machine applications on a coupled pair of the plurality of connected resource nodes of the storage area network.

2. The computer program of claim 1, wherein determining coupled placement is performed by an individual greedy algorithm.

3. The computer program of claim 1, wherein determining coupled placement is performed by a pair greedy algorithm.

4. The computer program of claim 1, wherein determining coupled placement is performed by a stable marriage algorithm.

5. The computer program of claim 1, wherein determining coupled placement operates considering different coupled pairs of the plurality of connected resource nodes of the storage area network have varying degrees of affinity for one another.

6. The computer program of claim 1, wherein determining coupled placement operates considering the coupled pair of the plurality of connected resource nodes of the storage area network have a distance factor between one another.

7. The computer program of claim 1, wherein determining coupled placement operates considering the applications each require a specified throughput between the coupled pair of the plurality of connected resource nodes of the storage area network.

8. The computer program of claim 1, wherein determining coupled placement operates to minimize a cost factor based on a specified throughput and a distance factor between the coupled pair of the plurality of connected resource nodes of the storage area network for each of the applications.

9. The computer program of claim 1, wherein the plurality of connected resource nodes comprises networked computer devices selected from the group consisting of host computers, switches, fabric nodes and storage subsystems of the SAN.

10. A method comprising the steps of:

receiving a resource graph describing a storage area network (SAN), the resource graph comprising a plurality of connected resource nodes each providing one or more resources where the resources include processing capability and storage capability for virtual machine applications;

receiving the applications each having a processing requirement element and a storage requirement element; and

determining coupled placement of the processing requirement element and the storage requirement element of each of the virtual machine applications on a coupled pair of the plurality of connected resource nodes of the storage area network.

11. The method of claim 10, wherein determining coupled placement is performed by an individual greedy algorithm.

12. The method of claim 10, wherein determining coupled placement is performed by a pair greedy algorithm.

13. The method of claim 10, wherein determining coupled placement is performed by a stable marriage algorithm.

14. The method of claim 10, wherein determining coupled placement operates considering different coupled pairs of the plurality of connected resource nodes of the storage area network have varying degrees of affinity for one another.

15. The method of claim 10, wherein determining coupled placement operates considering the coupled pair of the plurality of connected resource nodes of the storage area network have a distance factor between one another.

16. The method of claim 10, wherein determining coupled placement operates considering the applications each require a specified throughput between the coupled pair of the plurality of connected resource nodes of the storage area network.

17. The method of claim 10, wherein determining coupled placement operates to minimize a cost factor based on a specified throughput and a distance factor between the coupled pair of the plurality of connected resource nodes of the storage area network for each of the applications.

18. The method of claim 10, wherein the plurality of connected resource nodes comprises networked computer devices selected from the group consisting of host computers, switches, fabric nodes and storage subsystems of the SAN.

19. A placement system, comprising:

a memory for storing a resource graph describing a storage area network (SAN), the resource graph comprising a plurality of connected resource nodes each providing one or more resources where the resources include processing capability and storage capability for virtual machine applications and for storing the virtual machine applications each having a processing requirement element and a storage requirement element; and

a processor for determining coupled placement of the processing requirement element and the storage requirement element of each of the virtual machine applications on a coupled pair of the plurality of connected resource nodes of the storage area network.

20. The system of claim 19, wherein the processor determines coupled placement by minimizing a cost factor based on a specified throughput and a distance factor between the coupled pair of the plurality of connected resource nodes of the storage area network for each of the applications.