Real-Time Systems

, Volume 19, Issue 3, pp 283–302 | Cite as

Improving Predictability of Transaction Execution Times in Real-time Databases

  • Rajeev Rastogi
  • S. Seshadri
  • Philip Bohannon
  • Dennis Leinbaugh
  • Avi Silberschatz
  • S. Sudarshan

Abstract

We present a design for multi-versionconcurrency control and recovery in a main memory database, anddescribe logical and physical versioning schemes that allowread-only transactions to execute without obtaining data itemlocks or system latches. Our schemes enable a system to providethe guarantee that updaters will never interfere with read-onlytransactions, and read-only transactions will not be delayeddue to data contention. Consequently, transaction executionsbecome more predictable—this partially alleviates a majorproblem in real-time database system (RTDBS) scheduling, namely,significant unpredictability in transaction execution times.As a result, in addition to a transaction's deadline, a moreaccurate estimate of its execution time can also be taken intoaccount, thus facilitating better scheduling decisions. Our contributionsinclude several space saving techniques for the main-memory implementation,including improved methods for logical aging of data items andthe introduction of physical aging for low-level structures.Some of these schemes have been implemented on a widely-usedsoftware platform within Lucent, and the full scheme is implementedin the Dalí main-memory storage manager.

transactions versioning concurrency-control aging consistency locking timestamps deadlines 

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References

  1. Abbott, R., and Garcia-Molina, H. 1988. Scheduling real-time transactions: A performance evaluation. In Procs. of the International Conf. on Very Large Databases.Google Scholar
  2. Abbott, R., and Garcia-Molina, H. 1989. Scheduling real-time transactions with disk-resident data. In Procs. of the International Conf. on Very Large Databases.Google Scholar
  3. Agrawal, D., and Sengupta, S. 1989. Modular synchronization in multiversion databases: Version control and concurrency control. ACM SIGMOD Conf. on the Management of Data 89, (Portland OR), -Jun May.Google Scholar
  4. Aho, A., Hopcroft, J., and Ullman, J. D. 1974. The Design and Analysis of Computer Algorithm. Addison-Wesley.Google Scholar
  5. Bayer, R., Heller, H., and Reiser, A. 1980. Parallelism and recovery in database systems. ACMTrans. on Database Systems 5(2): 139–156. June.Google Scholar
  6. Bernstein, P. A., and Goodman, N. 1983. Multiversion concurrency control — theory and algorithms. ACM Transactions on Database Systems 8(4): 465–483. December.Google Scholar
  7. Bober, P., and Carey, M. 1992. On mixing queries and transactions via multiversion locking. In Proc. IEEE CS Intl. Conf. on Data Engineering 8, Tempe, AZ. February.Google Scholar
  8. Bober, P., and Carey, M. 1992. Multiversion query locking. In Proceedings of the Conference on Very Large Databases 18, Vancouver. Los Altos, CA: Morgan Kaufman. August.Google Scholar
  9. Bohannon, P., Leinbaugh, D., Rastogi, R., Seshadri, S., Silberschatz, A., and Sudarshan, S. 1995. Logical and physical versioning in main memory databases. Technical Report 113880-951031-12, AT&T Bell Laboratories, Murray Hill.Google Scholar
  10. Chan, A., Fox, S., Lin, W-T.K., Nori, A., and Ries, D. R. 1982. The implementation of an integrated concurrency control and recovery scheme. In ACM SIGMOD Conf. on the Management of Data 82, Orlando FL, pp. 184–191. June.Google Scholar
  11. DeWitt, D. J., Katz, R., Olken, F., Shapiro, D., Stonebraker, M., and Wood, D. 1984. Implementation techniques for main memory database systems. Proc. ACM-SIGMOD 1984 Int'l Conf. on Management of Data. pp. 1–8. June.Google Scholar
  12. Gottemukkala, V., and Lehman, T. 1992. Locking and latching in a memory-resident database system. In Proceedings of the Eighteenth International Conference on Very Large Databases, Vancouver, pp. 533–544. August.Google Scholar
  13. Hadzilacos, T. 1988. Serialization graph algorithms for multiversion concurrency control. In Proceedings of the ACM SIGACT-SIGART-SIGMOD Symposium on Principles of Database Systems. pp. 135–141. March.Google Scholar
  14. Haritsa, J., Carey, M., and Livny, M. 1990. Dynamic real-time optimistic concurrency control. In Proceedings of the IEEE Real-Time Systems Symposium.Google Scholar
  15. Haritsa, J., Carey, M., and Livny, M. 1990. On being optimistic about real-time constraints. In Proceedings of the ACM SIGACT-SIGART-SIGMOD Symposium on Principles of Database Systems.Google Scholar
  16. Haritsa, J., Carey, M., and Livny, M. 1993. Value-based scheduling in real-time database systems. VLDB Journal 2(2): 117–152.Google Scholar
  17. Huang, J., Stankovic, J., Ramamritham, K., and Townsley, D. 1989. Experimental evaluation of real-time transaction processing. In Proceedings of the IEEE Real-Time Systems Symposium.Google Scholar
  18. Huang, J., Stankovic, J., Ramamritham, K., and Townsley, D. 1991. On using priority inheritance in real-time databases. In Proceedings of the IEEE Real-Time Systems Symposium.Google Scholar
  19. Ibaraki, T., Kameda, T., and Katoh, N. 1990. Multiversion cautious schedulers for database concurrency control. IEEE Transactions on Software Engineering (SE),; ACM Computing Reviews 9012-0981. 16(3). March.Google Scholar
  20. Jagadish, H. V., Liuwen, D., Rastogi, R., Silberschatz, A., and Sudarshan, S. 1994. Dali: A high performance main-memory storage manager. In Procs. of the International Conf. on Very Large Databases.Google Scholar
  21. Kim, Y., and Son, S. H. 1996. Supporting predictability in real-time database systems. In Proceedings of the IEEE Real-Time Technology and Applications Symposium.Google Scholar
  22. Kung, H. T., and Lehman, P. L. 1980. Concurrent manipulation of binary search trees. ACM Transactions on Database Systems 5(3): 354–382. September.Google Scholar
  23. Lam, K., Son, S. H., Lee, V., and Hung, S. 1998. Using separate algorithms to process read-only transactions in real-time systems. In Proceedings of the IEEE Real-Time Systems Symposium.Google Scholar
  24. Lehman, T. J., and Carey, M. J. 1986. A study of index structures for main memory database management systems. In Proceedings of the Conference on very Large Databases 12, Kyoto, pp. 294–303. Los Altos, CA: Morgan Kaufman. August.Google Scholar
  25. Lehman, T., Shekita, E. J., and Cabrera, L. 1992. An evaluation of Starburst's memory resident storage component. IEEE Transactions on Knowledge and Data Engineering 4(6): 555–566. December.Google Scholar
  26. Manber, U., and Ladner, G. D. 1982. Concurrency control in dynamic search structures. ACM Proc. on Database Systems, Boston, pp. 268–282. April.Google Scholar
  27. Mohan, C., and Levine, F. 1992. Aries/im an efficient and high concurrency index management method using write-ahead logging. In ACM SIGMOD Conf. on the Management of Data 92, San Diego, June.Google Scholar
  28. Mohan, C., Pirahesh, H., and Lorte, R. 1992. Efficient and flexible methods for transient versioning of records to avoid locking by read-only transactions. In ACM SIGMOD Conf. on the Management of Data 92, San Diego, June.Google Scholar
  29. Ramamritham, K. 1993. Real-time databases. International Journal of Distributed and Parallel Databases 1: 199–226.Google Scholar
  30. Reed, D. P. 1978. Naming and synchronization in a decentralized computer system. Technical Report MIT-LCSTR-205. Cambridge: Massachusetts Institute of Technology. September.Google Scholar
  31. Salem, K., and Garcia-Molina, H. 1990. System M: A transaction processing testbed for memory resident data. IEEE Transactions on Knowledge and Data Engineering 2(1): 161–172. March.Google Scholar
  32. Shasha, D., and Goodman, N. 1988. Concurrent search structure algorithms. ACM Transactions on Database Systems 13(1): 53–90, March.Google Scholar
  33. Stankovic, J., and Zhao, W. 1988. On real-time transactions. ACM Sigmod Record 17(1): 4–18.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Rajeev Rastogi
    • 1
  • S. Seshadri
    • 1
  • Philip Bohannon
    • 1
  • Dennis Leinbaugh
    • 1
  • Avi Silberschatz
    • 1
  • S. Sudarshan
    • 2
  1. 1.Bell LaboratoriesMurray Hill
  2. 2.Computer Science and Engineering Dept.Indian Institute of TechnologyBombayIndia

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