COST AND POWER EFFICIENT STORAGE AREA NETWORK PROVISIONING

• US 20110238672A1
• Filed: 03/29/2010
• Published: 09/29/2011
• Est. Priority Date: 03/29/2010
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Gunatilaka, Harsha D., Agarwala, Sandip, Routray, Ramani R.
• Granted Patent: US 8,515,967 B2
• Time in Patent Office: Days
• US Class Current: 707/748
• 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

Various embodiments for efficiently provisioning a storage area network (SAN) are provided. In one embodiment, SAN information is provided to an engine for optimization. The SAN information includes at least one of SAN configuration information, SAN usage information, at least one cost profile, and at least one chargeback model. Based on the SAN information, those of an available plurality of storage resources not meeting at least one storage criterion are filtered. The filtered storage resources are ranked on a cost basis. A resource configuration graph is constructed based on the ranked storage resources. The resource configuration graph is traversed to obtain a plurality of possible SAN configuration plans. At least one power profile is applied to the plurality of possible SAN configuration plans to rank the plurality of possible SAN configuration plans by energy consumption.

Claims

1. A method for efficiently provisioning a storage area network (SAN) by a processor device, comprising:

providing SAN information to an engine for optimization, wherein the SAN information includes at least one of SAN configuration information, SAN usage information, at least one cost profile, and at least one chargeback model;

based on the SAN information, filtering those of an available plurality of storage resources not meeting at least one storage criterion;

ranking the filtered storage resources on a cost basis;

constructing a resource configuration graph based on the ranked storage resources;

traversing the resource configuration graph to obtain a plurality of possible SAN configuration plans; and

applying at least one power profile to the plurality of possible SAN configuration plans to rank the plurality of possible SAN configuration plans by energy consumption.

2. The method of claim 1, further including grouping the ranked plurality of possible SAN configuration plans by a user-defined attribute.

3. The method of claim 1, further including providing the ranked plurality of possible SAN configuration plans to a user.

4. The method of claim 1, further including selecting one of the ranked plurality of possible SAN configuration plans having a lowest energy consumption.

5. The method of claim 1, wherein applying the at least one power profile to the plurality of possible SAN configuration plans includes applying at least one of a workload-based power model, a spreadsheet-based power model, an analytical model, and a heuristic model.

6. The method of claim 5, wherein applying at least one of a workload-based power model includes considering at least one of a power constraint, space constraint, performance constraint, and resiliency constraint.

7. The method of claim 1, wherein ranking the filtered storage resources on the cost basis includes ranking the filtered storage resources on at least one of a total cost, subsystem type, fabric, multipath factor, and copy services basis.

8. The method of claim 1, wherein ranking the filtered storage resources on the cost basis includes considering a user-defined cost constraint.

9. A system for efficiently provisioning a storage area network (SAN), comprising:

a storage management module operational in the SAN, wherein the storage management module is adapted for;

providing SAN information to an engine for optimization, wherein the SAN information includes at least one of SAN configuration information, SAN usage information, at least one cost profile, and at least one chargeback model,

based on the SAN information, filtering those of an available plurality of storage resources not meeting at least one storage criterion,

ranking the filtered storage resources on a cost basis,

constructing a resource configuration graph based on the ranked storage resources,

traversing the resource configuration graph to obtain a plurality of possible SAN configuration plans, and

applying at least one power profile to the plurality of possible SAN configuration plans to rank the plurality of possible SAN configuration plans by energy consumption.

10. The system of claim 9, wherein the storage management module is further adapted for grouping the ranked plurality of possible SAN configuration plans by a user-defined attribute.

11. The system of claim 9, wherein the storage management module is further adapted for providing the ranked plurality of possible SAN configuration plans to a user.

12. The system of claim 9, wherein the storage management module is further adapted for selecting one of the ranked plurality of possible SAN configuration plans having a lowest energy consumption.

13. The system of claim 9, wherein the storage management module is further adapted for applying at least one of a workload-based power model, a spreadsheet-based power model, an analytical model, and a heuristic model.

14. The system of claim 13, wherein the storage management module is further adapted for considering at least one of a power constraint, space constraint, performance constraint, and resiliency constraint.

15. The system of claim 9, wherein the storage management module is further adapted for ranking the filtered storage resources on at least one of a total cost, subsystem type, fabric, multipath factor, and copy services basis.

16. The system of claim 9, wherein the storage management module is further adapted for considering a user-defined cost constraint.

17. The system of claim 9, wherein the storage management module is operational as a storage management processor (SMP) in the SAN.

18. A computer program product for efficiently provisioning a storage area network (SAN) using a processor device, the computer program product comprising a computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

a first executable portion for providing SAN information to an engine for optimization, wherein the SAN information includes at least one of SAN configuration information, SAN usage information, at least one cost profile, and at least one chargeback model;

a second executable portion for, based on the SAN information, filtering those of an available plurality of storage resources not meeting at least one storage criterion;

a third executable portion for ranking the filtered storage resources on a cost basis;

a fourth executable portion for constructing a resource configuration graph based on the ranked storage resources;

a fifth executable portion for traversing the resource configuration graph to obtain a plurality of possible SAN configuration plans; and

a sixth executable portion for applying at least one power profile to the plurality of possible SAN configuration plans to rank the plurality of possible SAN configuration plans by energy consumption.

19. The computer program product of claim 18, further including a seventh executable portion for grouping the ranked plurality of possible SAN configuration plans by a user-defined attribute.

20. The computer program product of claim 18, further including a seventh executable portion for providing the ranked plurality of possible SAN configuration plans to a user.

21. The computer program product of claim 18, further including a seventh executable portion for selecting one of the ranked plurality of possible SAN configuration plans having a lowest energy consumption.

22. The computer program product of claim 18, further including a seventh executable portion for applying at least one of a workload-based power model, a spreadsheet-based power model, an analytical model, and a heuristic model.

23. The computer program product of claim 22, further including an eighth executable portion for considering at least one of a power constraint, space constraint, performance constraint, and resiliency constraint.

24. The computer program product of claim 18, further including a seventh executable portion for ranking the filtered storage resources on at least one of a total cost, subsystem type, fabric, multipath factor, and copy services basis.

25. The computer program product of claim 18, further including a seventh executable portion for considering a user-defined cost constraint.