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Divergence control for distributed database systems

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Abstract

This paper presents distributed divergence control algorithms for epsilon serializability for both homogeneous and heterogeneous distributed databases. Epsilon serializability allows for more concurrency by permitting non-serializable interleavings of database operations among epsilon transactions. We first present a strict 2-phase locking divergence control algorithm and an optimistic divergence control algorithm for a homogeneous distributed database system, where the local orderings of all the sub-transactions of a distributed epsilon transaction are the same. In such an environment, the total inconsistency of a distributed epsilon transaction is simply the sum of those of all its sub-transactions. We then describe a divergence control algorithm for a heterogeneous distributed database system, where the local orderings of all the sub-transactions of a distributed epsilon transaction may not be the same and the total inconsistency of a distributed epsilon transaction may be greater than the sum of those of all its sub-transactions. As a result, in addition to executing a local divergence control algorithm in each site to maintain the local inconsistency, a global mechanism is needed to take into account the additional inconsistency

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References

  1. D. Agrawal and S. Sengupta, “Modular synchronization in multiversion databases: Version control and concurrency control,” inProc. of ACM SIGMOD Int. Conf. on Management of Data, pages 408–417, 1989.

  2. D. Barbara and H. Garcia-Molina, “The demarcation protocol: A technique for maintaining linear arithmetic constraints in distributed database systems,” InProc. of Int. Conf. on Extending Database Technology, 1991.

  3. P.A. Bernstein, V. Hadzilacos, and N. Goodman,Concurrency Control and Recovery in Database Systems. Addison-Wesley, 1987.

  4. P.M. Bober and M.J. Carey, “On mixing queries and transactions via multiversion locking,” InProc. of Int. Conf. on Data Engineering, pp. 535–545, 1992.

  5. P.M. Bober and M.J. Carey, “Multiversion query locking,” inProc. of the 21st Int. Conf. on Very Large Data Bases, pp. 497–510, 1992.

  6. Y. Breitbart, D. Georgakopoulos, M. Rusinkiewicz, and A. Silberschatz, “On rigorous transaction scheduling,”IEEE Trans. on Software Engineering, SE-17(9):954–960, Sept. 1991.

    Google Scholar 

  7. M.J. Carey and W.A. Muhanna, “The performance of multiversion concurrency control algorithms,”ACM Trans. on Computer Systems, 4(4):338–378, Nov. 1986.

    Google Scholar 

  8. A. Chan and R. Gray, “Implementing distributed read-only transactions,”IEEE Trans. on Software Engineering, SE-11(2):205–212, Feb. 1985.

    Google Scholar 

  9. S.B. Davidson, H. Garcia-Molina, and D. Skeen, “Consistency in partitioned networks,”ACM Computing Surveys, 17(3):341–370, Sept. 1985.

    Google Scholar 

  10. A. Elmagarmid and W. Du, “A paradigm for concurrency control in heterogeneous distributed database systems,” inProc. of Int. Conf. on Data Engineering, pp. 37–46, 1990.

  11. H. Garcia-Molina and G. Wiederhold, “Read-only transactions in a distributed database,”ACM Trans. on Database Systems, 7(2):209–234, June 1982.

    Google Scholar 

  12. D. Georgakopoulos and M. Rusinkiewicz, “On serializability of multidatabase transactions through forced local conflicts,” inProc. of Int. Conf. on Data Engineering, pp. 314–323, 1991.

  13. L. Golubchik and A. Thomasian, “Token allocation in distributed systems,” inProc. of Int. Conf. on Distributed Computing Systems, pages 64–71, 1992.

  14. P.M. Herlihy and J.M. Wing, “Linearizability: A correctness condition for concurrent objects,”ACM Trans. on Programming Languages and Systems, 12(3):463–492, July 1990.

    Google Scholar 

  15. G.E. Kaiser and B. Hailpern, “An object-based programming model for shared data,”ACM Trans. on Programming Languages and Systems, 14(2):201–264, April 1992.

    Google Scholar 

  16. I. Krishnan and W. Zimmer, editors,IFIP TC6/WG6.6 2nd Int. Symp. on Integrated Network Management, 1991. North-Holland.

  17. B. Lindsay, “A retrospective of R*: A distributed database management system,”Proc. of the IEEE, 75(5):668–673, May 1987.

    Google Scholar 

  18. S. Mehrotra, R. Rastogi, Y. Breitbart, H.F. Korth and A. Silberschatz, “The concurrency control problem in multidatabases: Characteristics and solutions,” inProc. of ACM SIGMOD Int. Conf. on Management of Data, pp. 228–297, 1992.

  19. A. Merchant, K.-L. Wu, P.S. Yu, and M.-S. Chen, “Performance analysis of dynamic finite versioning for concurrent transaction and query processing,” inProc. of 1992 ACM SIGMETRICS Conf. on Measurement and Modeling of Computer Systems, pp. 103–114, 1992.

  20. C. Mohan, H. Pirahesh, and R. Lorie, “Efficient and flexible methods for transient versioning of records to avoid locking by read-only transactions,” inProc. of ACM SIGMOD Int. Conf. on Management of Data, pp. 124–133, 1992.

  21. P.E. O'Neil, “The escrow transaction model,”ACM Trans. on Database Systems, 11(4):405–430, Dec. 1986.

    Google Scholar 

  22. C. Pu, “Generalized transaction processing with epsilon-serializability,” InProc. of 4th Int. Workshop on High Performance Transaction Systems, 1991.

  23. C. Pu and A. Leff, “Replica control in distributed systems: An asynchronous approach,” inProc. of 1991 ACM SIGMOD Int. Conf. on Management of Data, pp. 377–386, 1991.

  24. C. Pu and A. Leff, “Autonomous transaction execution with epsilon-serializability,” inProc. of 1992 RIDE Workshop on Transaction and Query Processing, 1992.

  25. C. Pu, “Superdatabases for composition of heterogeneous databases,” in Amar Gupta, editor,Integration of Information Systems: Bridging Heterogeneous Databases, pp. 150–157, 1989.

  26. K. Ramamrithan and C. Pu, “A formal characterization of epsilon serializability,”IEEE Transactions on Knowledge and Data Engineering, to appear 1994.

  27. Y. Raz, “The principle of commitment ordering,” inProc. of the 18th Int. Conf. on Very Large Data Bases, pp. 292–312, 1992.

  28. D.P. Reed, “Implementing atomic actions on decentralized data,”ACM Trans. on Computer Systems, 1(1):3–23, Feb. 1983.

    Google Scholar 

  29. 1st Int. Conf. on Artificial Intelligence Applications on Wall Street, 1991.

  30. W.E. Weihl, “Distributed version management for read-only actions,”IEEE Trans. on Software Engineering, SE-13(1):55–64, Jan. 1987.

    Google Scholar 

  31. K.-L. Wu, P.S. Yu, and C. Pu, “Divergence control for epsilon-serializability,” inProc. of Int. Conf. on Data Engineering, pp. 506–515, 1992.

  32. K.-L. Wu, P.S. Yu, and M.-S. Chen, “Dynamic Finite Versioning: An effective versioning approach to concurrent transaction and query processing,” inProc. of Int. Conf. on Data Engineering, 1993.

  33. P.K. Chrysanthis and K. Ramamritham, “ACTA: A framework for specifying and reasoning about transaction structure and behavior,” InProc. of 1990 ACM SIGMOD Int. Conf. on Management of Data, pp. 194–203, May 1990.

  34. T.-W. Kuo and A. Mok, “Application semantics and concurrency control of real-time data-intensive applications,” inProc. of Real-Time Systems Symposium, pp. 35–45, 1992.

  35. K.-P. Eswaran, J.N. Gray, R.A. Lorie, and I.L. Traiger, “The Notions of Consistency and Predicate Locks in a Database System,”Communications of the ACM, 19(11):624–632, November 1976.

    Google Scholar 

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Author notes

  1. Calton Pu

    Present address: the Dept. of Computer Science and Engineering, Oregon Graduate Institute, 97006, Beaverton, OR

Authors and Affiliations

  1. Department of Computer Science, Columbia University, 10027, New York, NY

    Calton Pu, Wenwey Hseush & Gail E. Kaiser

  2. IBM T.J. Watson Research Center, P.O. Box 704, 10598, Yorktown Heights, NY

    Kun-Lung Wu & Philip S. Yu

Authors
  1. Calton Pu
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  2. Wenwey Hseush
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  3. Gail E. Kaiser
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  4. Kun-Lung Wu
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  5. Philip S. Yu
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Recommended by: Meichum Hsu

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Pu, C., Hseush, W., Kaiser, G.E. et al. Divergence control for distributed database systems. Distrib Parallel Databases 3, 85–109 (1995). https://doi.org/10.1007/BF01263658

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