PREDICTIVE MIGRATE AND RECALL

• US 20120096053A1
• Filed: 10/13/2010
• Published: 04/19/2012
• Est. Priority Date: 10/13/2010
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: LEHR, Douglas L., McCUNE, Franklin E., REED, David C., SMITH, Max D.
• Granted Patent: US 8,661,067 B2
• Time in Patent Office: Days
• US Class Current: 707/809
• CPC Class Codes: G06F 3/0613 in relation to throughput
• CPC Class Codes: G06F 3/0647 Migration mechanisms
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]

Abstract

Various embodiments for optimizing data migration and recall in a computing storage environment by a processor device are provided. Data stored in the computing storage environment is analyzed over a predetermined period of time to identify a usage pattern of a portion of the data. The portion of the data having the usage pattern is recalled in advance of a usage time, the usage time predicted by the usage pattern for the portion of the data to be accessed.

Claims

1. A method for optimizing data migration and recall in a computing storage environment, by a processor device, comprising:

analyzing data stored in the computing storage environment over a predetermined period of time to identify a usage pattern of a portion of the data; and

preemptively recalling the portion of the data having the usage pattern in advance of a usage time, the usage time predicted by the usage pattern for the portion of the data to be accessed.

2. The method of claim 1, wherein the analyzing the data further includes identifying portions of the data having been unused for an additional predetermined period of time.

3. The method of claim 2, wherein the analyzing the data further includes:

calculating a median amount of time the portion of the data is used during a usage window, and

adding the median amount to an additional time calculated from the median amount to generate a predictive usage length.

4. The method of claim 3, further including building a usage schedule from the usage length and the usage time, wherein the preemptive recall of the portion of the data is set based on the usage schedule.

5. The method of claim 1, wherein the analyzing the data further includes parsing through at least one of system management facility (SMF) records and migration logs.

6. The method of claim 1, wherein the analyzing the data further includes performing at least one of monitoring user logons to multiple virtual storage (MVS) systems and parsing through system management facility (SMF) records.

7. The method of claim 6, wherein the usage pattern of the portion of the data is calculated by determining if the portion is used more than a predetermined percentage per user logon over the predetermined period of time.

8. A system for optimizing data migration and recall in a computing storage environment, comprising:

a data set module operational in the computing storage environment, wherein the data set module is adapted for;

analyzing data stored in the computing storage environment over a predetermined period of time to identify a usage pattern of a portion of the data, and

preemptively recalling the portion of the data having the usage pattern in advance of a usage time, the usage time predicted by the usage pattern for the portion of the data to be accessed.

9. The system of claim 8, wherein the data set module is further adapted for, pursuant to analyzing the data, identifying portions of the data having been unused for an additional predetermined period of time.

10. The system of claim 9, wherein the data set module is further adapted for, pursuant to analyzing the data:

calculating a median amount of time the portion of the data is used during a usage window, and

adding the median amount to an additional time calculated from the median amount to generate a predictive usage length.

11. The system of claim 10, wherein the data set module is further adapted for building a usage schedule from the usage length and the usage time, wherein the preemptive recall of the portion of the data is set based on the usage schedule.

12. The system of claim 8, wherein the data set module is further adapted for, pursuant to analyzing the data, parsing through at least one of system management facility (SMF) records and migration logs.

13. The system of claim 8, wherein the data set module is further adapted for, pursuant to analyzing the data, performing at least one of monitoring user logons to multiple virtual storage (MVS) systems and parsing through system management facility (SMF) records.

14. The system of claim 13, wherein the usage pattern of the portion of the data is calculated by determining if the portion is used more than a predetermined percentage per user logon over the predetermined period of time.

15. A computer program product for optimizing data migration and recall in a computing storage environment, 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 analyzing data stored in the computing storage environment over a predetermined period of time to identify a usage pattern of a portion of the data; and

a second executable portion for preemptively recalling the portion of the data having the usage pattern in advance of a usage time, the usage time predicted by the usage pattern for the portion of the data to be accessed.

16. The computer program product of claim 15, further including a second executable portion for, pursuant to the analyzing the data, identifying portions of the data having been unused for an additional predetermined period of time.

17. The computer program product of claim 16, further including a third executable portion for, pursuant to analyzing the data:

calculating a median amount of time the portion of the data is used during a usage window, and

adding the median amount to an additional time calculated from the median amount to generate a predictive usage length.

18. The computer program product of claim 17, further including a fourth executable portion for building a usage schedule from the usage length and the usage time, wherein the preemptive recall of the portion of the data is set based on the usage schedule.

19. The computer program product of claim 15, further including a third executable portion for, pursuant to the analyzing the data, parsing through at least one of system management facility (SMF) records and migration logs.

20. The computer program product of claim 15, further including a third executable portion for, pursuant to the analyzing the data, performing at least one of monitoring user logons to multiple virtual storage (MVS) systems and parsing through system management facility (SMF) records.

21. The computer program product of claim 20, wherein the usage pattern of the portion of the data is calculated by determining if the portion is used more than a predetermined percentage per user logon over the predetermined period of time.