Data Update Management in a Cloud Computing Environment

• US 20140244896A1
• Filed: 02/26/2013
• Published: 08/28/2014
• Est. Priority Date: 02/26/2013
• Status: Active Grant

• Current Assignee: Seagate Technology LLC (Seagate Technology Holdings Plc)
• Original Assignee: Seagate Technology LLC (Seagate Technology Holdings Plc)
• Inventors: Goss, Ryan James, Ebsen, David Scott, Gaertner, Mark Allen, Steiner, Michael Joseph, Khoueir, Antoine
• Granted Patent: US 11,687,292 B2
• Time in Patent Office: Days
• US Class Current: 711/103
• CPC Class Codes: G06F 3/0611 in relation to response time
• CPC Class Codes: G06F 3/0619 in relation to data integrity, e.g. data losses, bit errors
• CPC Class Codes: G06F 3/0649 Lifecycle management
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: G06F 3/0685 Hybrid storage combining heterogeneous device types, e.g. hierarchical storage, hybrid arrays

Abstract

Method and apparatus for managing data in a cloud computing environment. In accordance with some embodiments, data updates are received to a multi-tier memory structure across a cloud network and stored as working data in an upper rewritable non-volatile memory tier of the memory structure. The working data are periodically logged to a lower non-volatile memory tier in the memory structure while a current version of the working data remain in the upper memory tier. The upper and lower memory tiers each are formed of rewritable memory cells having different constructions and storage attributes.

Claims

1. A method comprising:

receiving data updates to a multi-tier memory structure across a cloud network and storing the received data updates as working data in an upper rewritable non-volatile memory tier of the memory structure; and

logging the working data to a lower non-volatile memory tier in the memory structure, the upper and lower memory tiers each comprising rewritable memory cells having different constructions and storage attributes.

2. The method of claim 1, further comprising migrating the working data from a first location to a second location in the upper memory tier and resetting all of the rewritable memory cells at the first location to a known programming state.

3. The method of claim 1, in which the logged data updates comprise snapshots of a then current version of the working data, wherein the working data are migrated to a new location in the upper memory tier concurrently with the logging of the data updates.

4. The method of claim 1, further comprising generating a session log of the access operations executed upon the working data during a cloud computing session and storing the session log in a lower memory tier of the memory structure.

5. The method of claim 4, in which the session log comprises a command history table that identifies read and write operations executed during the session in sequential order and an elapsed time interval between each pair of successive commands.

6. The method of claim 5, in which the session log further comprises at least one copy of a data block from the working data identified as having high level of interest, wherein the at least one copy of the data block is stored as retained data in the lower memory tier.

7. The method of claim 1, further comprising analyzing a sequence of access operations upon the working data and initiating a prefetch command script to speculatively request selected data in anticipation of a future request for said selected data.

8. The method of claim 7, in which the request for the selected data is issued to a lower tier of the multi-tier memory structure.

9. The method of claim 7, in which the request for the selected data is issued to a remote node in the cloud computing network.

10. An apparatus comprising:

a multi-tier memory structure comprising a plurality of non-volatile memory tiers each having different data transfer attributes and corresponding rewritable memory cell constructions and storage attributes; and

a storage manager adapted to store data updates received across a cloud network as working data in an upper non-volatile memory tier of the memory structure, and to log the working data to a lower non-volatile memory tier in the memory structure.

11. The apparatus of claim 10, in which the storage manager comprises a data log circuit that logs the working data to the lower memory tier and concurrently performs a garbage collection operation to migrate the working data from a first location to a second location in the upper memory tier and reset all of the rewritable memory cells at the first location to a known programming state.

12. The apparatus of claim 10, in which the logged data updates comprise snapshots of a then current version of the working data, wherein the snapshots are logged as a part of the garbage collection operation.

13. The apparatus of claim 10, in which the storage manager comprises a session log circuit adapted to generate a session log of the access operations executed upon the working data during a cloud computing session and store the session log in a lower non-volatile memory tier of the memory structure.

14. The apparatus of claim 13, in which the session log comprises a command history table that identifies read and write operations executed during the session in sequential order and an elapsed time interval between each pair of successive commands.

15. The apparatus of claim 14, in which the session log further comprises at least one copy of a data block from the working data identified as having high level of interest, wherein the at least one copy of the data block is stored as retained data in the lower memory tier.

16. The apparatus of claim 10, in which the storage manager comprises a data pattern analysis engine adapted to analyze a sequence of access operations upon the working data and initiate a prefetch command script to speculatively request selected data in anticipation of a future request for said selected data.

17. The apparatus of claim 16, in which the request for the selected data is issued to a lower tier of the multi-tier memory structure.

18. The apparatus of claim 16, in which the request for the selected data is issued to a remote node in the cloud computing network.

19. The apparatus of claim 16, in which the data pattern analysis engine stores the prefetch command script and retained data blocks from the working data previously identified as having a relatively high level of interest in a lower memory tier of the memory structure, wherein the data pattern analysis engine detects subsequent execution of a previous session and initiates the prefetch command script to transfer the retained data blocks to the upper memory tier and to request additional prefetch data blocks from a remote node in the cloud network.

20. The apparatus of claim 10, in which the upper memory tier comprises a selected one of STRAM, PCRAM or RRAM rewritable non-volatile memory cells, and the lower memory tier comprises a different selected one of STRAM, PCRAM or RRAM rewritable non-volatile memory cells.