INTELLIGENT TIERS OF BACKUP DATA

• US 20100274983A1
• Filed: 04/24/2009
• Published: 10/28/2010
• Est. Priority Date: 04/24/2009
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Mehr, John D., Murphy, Elissa E. S.
• Granted Patent: US 8,769,049 B2
• Time in Patent Office: Days
• US Class Current: 711/162
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 11/1448 Management of the data involved in backup or backup restore
• CPC Class Codes: G06F 11/1451 by selection of backup contents
• CPC Class Codes: G06F 11/1456 Hardware arrangements for backup
• CPC Class Codes: G06F 11/1464 for networked environments
• CPC Class Codes: G06F 11/1469 Backup restoration techniques
• CPC Class Codes: G06F 11/2094 Redundant storage or storage space G06F11/2056 takes precedence
• CPC Class Codes: G06F 11/3034 where the computing system component is a storage system, e.g. DASD based or network based digital input from or digital output to record carriers G06F3/06; digital recording or reproducing G11B20/18; 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], H04L67/1097
• CPC Class Codes: G06F 11/3433 for load management allocation of a server based on load conditions G06F9/505; load rebalancing G06F9/5083; redistributing the load in a network by a load balancer H04L67/1029
• CPC Class Codes: G06F 11/3485 for I/O devices
• CPC Class Codes: G06F 11/3495 for systems
• CPC Class Codes: G06F 2201/815 Virtual
• CPC Class Codes: G06F 2201/86 Event-based monitoring
• CPC Class Codes: G06F 2201/875 Monitoring of systems including the internet
• CPC Class Codes: G06F 2201/885 Monitoring specific for caches

Abstract

The claimed subject matter relates to systems and/or methodologies that facilitate intelligent distribution of backup information across storage locations in network-based backup architectures. A virtual layering of backup information across storage locations in the backup architecture can be implemented. Statistical models are utilized to dynamically re-allocate backup information among storage locations and/or layers to ensure availability of data, minimum latency upon restore, and minimum bandwidth utilization upon restore. In addition, heuristics or machine learning techniques can be applied to proactively detect failures or other changes in storage locations such that backup information can be reallocated accordingly prior to a failure.

Claims

1. A system that facilitates intelligent allocation of backup data among a set of storage locations in a backup environment, comprising:

a processor coupled to a memory that retains computer-executable instructions, the processor executes;

a monitor component that identifies at least one of properties of backup data stored by one or more storage locations or properties of the one or more storage locations; and

a tier component that implements virtual layers of backup data across the one or more storage locations in accordance with the properties of the backup data or properties of the storage locations, the tier component distributes backup data among the one or more storage locations to ensure availability while reducing storage utilization and latency upon restore.

2. The system of claim 1, wherein the monitor component includes a data evaluation component the analyzes backup data to ascertain the properties of the backup data.

3. The system of claim 1, wherein the monitor component includes a machine evaluation component that observes the one or more storage locations to determine the properties of the one or more storage locations.

4. The system of claim 1, wherein the tier component includes a distribution component that replicates block of backup data to the one or more storage nodes based at least in part on the properties of the backup data or the storage locations.

5. The system of claim 1, wherein the tier component includes an indexing component that maintains an index, the indexing component at least one of adds, deletes, or modifies entries in the index when distribution decisions are rendered by the tier component.

6. The system of claim 5, wherein the index comprises a listing of relationships between backup versions and storage locations to which the backup versions have been distributed.

7. The system of claim 1, wherein the properties of the backup data include at least one of frequency of access to the backup data, availability of the backup data, or time since creation of the backup data.

8. The system of claim 7, wherein frequently accessed backup data is inferred to be most likely to be restored.

9. The system of claim 8, wherein the tier component distributes frequently accessed data to storage locations in close network proximity to a restore client.

10. The system of claim 8, wherein the tier component replicates copies of frequently accessed backup data to reliable storage locations.

11. The system of claim 7, wherein infrequently accessed backup data is inferred to be least likely to be restored.

12. The system of claim 11, wherein the tier component allocates infrequently accessed backup data to remote storage nodes that provide reliable storage.

13. The system of claim 1, wherein the properties of the storage locations include health of respective storage locations, storage capacity of storage locations, availability of storage locations, bandwidth utilization of storage locations, or predicted latency times for transmission of data between respective storage locations.

14. The system of claim 1, wherein the tier component detects critical failure of at least one of a storage location or a client machine based upon the properties of the one or more storage locations.

15. The system of claim 14, wherein the tier component proactively allocates backup data in response to the detected critical failure.

16. The system of claim 1, wherein the one or more storage locations include one or more of peers or cloud storage locations.

17. The system of claim 16, wherein the tier component creates the virtual layers of the backup data through application of a higher level of preference on storage locations corresponding to peers than to storage locations corresponding to cloud storage locations.

18. A method for intelligently tiering backup information in a distributed backup environment, comprising:

employing a processor executing computer-executable instructions stored on a computer-readable storage medium to implement the following acts;

creating virtual layers of backup information across a set of storage locations;

monitoring backup information to ascertain properties of the backup information, the properties include at least one of access frequency, availability, or age of the backup information; and

dynamically reallocating backup information across the virtual layers, based upon the properties of the backup information, to ensure availability of the backup information while minimizing storage costs and latency upon restoration of the backup information.

19. The method of claim 18, further comprising:

designating the backup information as at least one of hot data or cold data based upon the properties of the backup information;

allocating hot data to storage locations that provide optimal locality to a restore client; and

allocating cold data to remote storage locations that provide storage at minimum cost.

20. A system that facilitates intelligent distribution of backup information across a set of storage locations, comprising:

at least one processor that executes computer-executable code stored in memory to effect the following;

means for identifying properties of backup data stored in a set of storage locations, the set of storage locations include one or more peers, super peers, or cloud storage locations, the properties include frequency of access to the backup data, number of copies of the backup data stored in the set of storage locations, and age of the backup data;

means for applying heuristics to the properties of the backup data to discover access patterns; and

means for reallocating backup data among the set of storage locations in accordance with discovered access patterns such that frequently accessed data is replicated among at least one of peers or super peers and infrequently accessed data is shifted to a cloud storage location.