Localized-access protocols for replicated databases

  • D. Agrawal
  • A. El Abbadi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 486)

Abstract

In this paper, we present two protocols for efficient execution of transactions in replicated databases. Transactions are executed at a single site thus avoiding communication overhead and distributed commitment, which are required by most other replica control protocols. In the first protocol, data accessibility at a site can be dynamically reconfigured using special transactions, which are executed on demand. In the second protocol, data accessibility is reconfigured by migrating ownership of individual objects in the database. The two protocols present trade-offs with respect to atomicity, resiliency, and data availability. The approach of local execution of user transactions improves response time, eliminates the need for distributed commit protocols, and accommodates database heterogeneity.

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References

  1. [AE90]
    D. Agrawal and A. El Abbadi. Locks with Constrained Sharing. In Proceedings of the Ninth ACM Symposium on Principles of Database Systems, pages 85–93, April 1990.Google Scholar
  2. [BAA89]
    J.M. Bernabéu-Aubán and M. Ahamad. Applying a Path-Compression Technique to Obtain an Efficient Distributed Mutual Exclusion Algorithm. In Proceedings of the Third International Workshop on Distributed Algorithms, pages 33–44, September 1989.Google Scholar
  3. [BG87]
    P. A. Bernstein and N. Goodman. A Proof Technique for Concurrency Control and Recovery Algorithms for Replicated Databases. Distributed Computing, Springer-Verlag, 2(1):32–44, January 1987.Google Scholar
  4. [CR83]
    O. Carvalho and G. Roucairol. On Mutual Exclusion in Computer Networks. Communications of the ACM, 26:146–147, February 1983.Google Scholar
  5. [DGMS85]
    S. B. Davidson, H. Garcia-Molina, and D. Skeen. Consistency in partitioned networks. ACM Computing Surveys, 17(3):341–370, September 1985.Google Scholar
  6. [EGLT76]
    K. P. Eswaran, J. N. Gray, R. A. Lorie, and I. L. Traiger. The Notion of Consistency and Predicate Locks in Database System. Communications of the ACM, 19(11):624–633, November 1976.Google Scholar
  7. [ESC85]
    A. El Abbadi, D. Skeen, and F. Cristian. An Efficient Fault-Tolerant Protocol for Replicated Data Management. In Proceedings of the Fourth ACM Symposium on Principles of Database Systems, pages 215–228, March 1985.Google Scholar
  8. [ET89a]
    A. El Abbadi and S. Toueg. Maintaining Availability in Partitioned Replicated Databases. ACM Transaction on Database Systems, 14(2):264–290, June 1989.Google Scholar
  9. [ET89b]
    A. El Abbadi and S. Toueg. The Group Paradigm for Concurrency Control Protocol. IEEE Transactions on Knowledge and Data Engineering, pages 376–386, September 1989.Google Scholar
  10. [Gif79]
    D. K. Gifford. Weighted Voting for Replicated Data. In Proceedings of the Seventh ACM Symposium on Operating Systems Principles, pages 150–159, December 1979.Google Scholar
  11. [Her87]
    M. Herlihy. Dynamic Quorum Adjustments for Partitioned Data. ACM Transactions on Database Systems, 12(2):170–194, June 1987.Google Scholar
  12. [KGM87]
    B. Kogan and H. Garcia-Molina. Update Propagation in Bakunin Data Networks. In Proceedings of the Sixth ACM Symposium on Principles of Distributed Computing, pages 13–26, August 1987.Google Scholar
  13. [KR81]
    H. T. Kung and J. T. Robinson. On Optimistic Methods for Concurrency Control. ACM Transactions on Database Systems, 6(2):213–226, June 1981.Google Scholar
  14. [Lam78]
    L. Lamport. Time, Clocks, and the Ordering of Events in a Distributed System. Communications of the ACM, 21(7):558–565, July 1978.Google Scholar
  15. [LH89]
    K. Li and P. Hudak. Memory Coherence in Shared Virtual Memory Systems. ACM Transactions on Computer Systems, 7(4), November 1989.Google Scholar
  16. [OL88]
    B. Oki and B. Liskov. Viewstamped Replication: A New Primary Copy Method to Support Highly-Available Distributed Systems. In Proceedings of the Seventh ACM Symposium on Principles of Distributed Computing, pages 8–17, August 1988.Google Scholar
  17. [Ray89]
    K. Raymond. A Tree-Based Algorithm for Distributed Mutual Exclusion. ACM Transactions on Computer Systems, 7(1):61–77, February 1989.Google Scholar
  18. [Ree78]
    D. P. Reed. Naming and Synchronization in a Decentralized Computer System. Technical Report MIT-LCS-TR-205, Massachusetts Institute of Technology, Cambridge, Massachusetts, September 1978.Google Scholar
  19. [SK85]
    I. Suzuki and T. Kasami. A Distributed Mutual Exclusion Algorithm. ACM Transactions on Computer Systems, 3(4):344–349, November 1985.Google Scholar
  20. [Ske82]
    D. Skeen. Crash Recovery in a Distributed Database Systems. PhD thesis, Department of Electrical Engineering and Computer Science, University of California at Berkeley, 1982.Google Scholar
  21. [SS82]
    R. Schlichting and F. B. Schneider. Fail-Stop Processors: An Approach to Designing Fault-Tolerant Computing Systems. ACM Transactions on Computer Systems, 1(3):222–238, August 1982.Google Scholar
  22. [SS90]
    N. Soparkar and A. Silberschatz. Data-value Partitioning and Virtual Messages. In Proceedings of the Ninth ACM Symposium on Principles of Database Systems, pages 357–367, April 1990.Google Scholar
  23. [Sto79]
    M. Stonebraker. Concurrency Control and Consistency in Multiple Copies of Data in Distributed INGRES. IEEE Transactions on Software Engineering, 3(3):188–194, May 1979.Google Scholar
  24. [TH90]
    V. O. Tam and M. Hsu. Token Transactions: Managing Fine-Grained Migration of Data. In Proceedings of the Ninth ACM Symposium on Principles of Database Systems, pages 344–356, April 1990.Google Scholar

Copyright information

© Springer-Verlag 1991

Authors and Affiliations

  • D. Agrawal
    • 1
  • A. El Abbadi
    • 1
  1. 1.Department of Computer ScienceUniversity of CaliforniaSanta Barbara

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