1. 6.4 Data And File Replication Presenter : Jing He Instructor: Dr. Yanqing Zhang

2. Outline Basic Knowledge Most Recent Projects Future Works References

3. Outline Basic Knowledge Most Recent Projects Future Works References

4. Why replicate Performance Reliability Resource sharing Network resource saving

5. Challenge Transparency –Parallelism transparency –Failure transparency –Replication transparency Concurrent Control Failure Recovery

6. Goal One-copy serializability: –The execution of transaction on replicated objects is equivalent to the execution of the same transactions on non-replicated objects [1][R. Chow et al. 1997 ].

7. Architecture FSA, File service agent, client interface RM, replica manager, provide replication functions Client chooses one or more FSA to access data object. FSA acts as front end to replica managers RMs to provide replication transparency. FSA contacts one or more RMs for actual updating and reading of data objects.

8. Architecture

9. Read operations Read-one-primary: FSA only read from a primary RM to enforce consistency Read-one: FSA may read from any RM to gain concurrency Read-quorum: FSA must read from a quorum of RMs to decide the currency of data

10. Write Operations Write-one-primary: only write to primary RM, primary RM update all other RMs Write-all: update to all RMs Write-all- available: write to all functioning RMs. Faulty RM need to be synched before bring online.

11. Write Operations Cont. Write-quorum: update to a predefined quorum of RMs Write-gossip: update to any RM and lazily propagated to other RMs

12. Read-one-primary, write-one-primary Other RMs are backups of primary RM No concurrency Easy serialized Simple to implement Achieve one-copy serializability Primary RM is performance bottleneck

13. Read-one, Write-all Provides concurrency Concurrency control protocol needed to ensure consistency (serialization) Achieve one-copy serializability Difficult to implement (there will be failed TM to block any updates)

14. Read-one, Write-all-available Variation of Read one, Write all May not guarantee one-copy serializability Issue of lots conflict in transactions

15. Read-quorum, Write-quorum Version number attached to replicated object Highest version numbered object is the latest object in read. Write operation advances version by 1 Write-write conflict: 2 * Write quorum > all object copies Read-write conflict: Write quorum + read quorum > all object copies

16. Gossip Update Updates are less frequent than reads,updates can be propagated lazily to replicas. Both read and update operations are directed by FSA to any RM FSA shields replication details from clients. Increased performance Typical read one, write gossip Use timestamp

17. Basic Gossip Update Read: if TS fsa <=TS rm, RM has recent data, return it, otherwise wait for gossip, or try other RM Update: if Ts fsa >TS rm, update. Update TS rm send gossip. Otherwise, process based on application, perform update or reject Gossip: update RM if gossip carries new updates.

18. Causal Order Gossip Protocol Used for read-modify In a fixed RM configuration Using vector timestamps Using buffer to keep the order

19. Disadvantages of File replication Contents of the file needs to be known before replication operation takes place. Existing System cant work in limited bandwidth networks. DFS replication will not work well when there are large number of changes to replicate.

20. Outline Basic Knowledge Most Recent Projects Future Works References

21. Current Project Data Grid File Replication [2][C. Yang, 2008] Create copies in convenient location Replicas are adjusted to appropriate locations using Bavesian Networks (BN) File replication in P2P systems Plover: making replicas among physically close nodes; load balance between replica nodes [3][H. Shen, 2009] EAD: efficient and adative decentralized file replication algorithm[4,5][H. Shen, 2009]

22. Outline Basic Knowledge Most Recent Projects Future Works References

23. Future Work Improve Efficiency and Effectiveness of file replication scheme Integrate File Replication and Consistency Maintenance

24. Outline Basic Knowledge Most Recent Projects Future Works References

25. Reference [1] R. Chow and T. Johnson, Distributed Operating Systems & Algorithms, 1997 [2] C. Yang, C. Huang, and T. Hsiao, A Data Grid File Relication Maintenance Strategy Using Bayesian Networks, Eight International Conference on Intelligent Systems Design and Application, 2008 [3] H. Shen, and Y. Zhu, A proactive low-overhead file replication scheme for structured P2P content delivery network, Journal Parallel Distributed Computing, 2009 [4] H. Shen, IRM: Integrated File Replication and Consistency Maintenance in P2P Systems, IEEE Transactions on Parallel and Distributed Systems, 2009 [5] H. Shen, An Efficient and Adaptive Decentralized File Replication Algorithm in P2P File Sharing Systems, IEEE Transactions on Parallel and Distributed Systems, 2009