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Static and dynamic data management in networks

  • Friedhelm Meyer auf der Heide
  • Berthold Vöcking
Invited Talks
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1300)

Abstract

We survey strategies for distributing shared objects in large parallel and distributed systems. Examples of such objects are global variables in a parallel program, pages or cache lines in a virtual shared memory system, shared files in a distributed file system, and videos and pictures in a distributed multimedia server. We focus on strategies for distributing, accessing, and (consistently) updating such objects. The strategies are provably efficient with respect to various cost measures. We describe and analyse static, hashing based schemes that minimize the contention at the memory modules in worst case scenarios. Especially, the benefit of redundant placement schemes is discussed. We further take network congestion and bandwidth into account. Here we present schemes that are provably efficient w.r.t. information about access frequencies. Further, dynamic schemes are presented which have good competitive ratio, i.e., are efficient compared to an optimal dynamic distribution that is constructed using full knowledge of the dynamic access pattern.

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References

  1. 1.
    B. Awerbuch, Y. Bartal, and A. Fiat. Competitive distributed file allocation. In Proc. of the 25th ACM Symp. on Theory of Computing (STOC), pages 164–173, 1993.Google Scholar
  2. 2.
    B. Awerbuch, Y. Bartal, and A. Fiat. Distributed paging for general networks. In Proc. of the 7th ACM Symp. on Discrete Algorithms (SODA), pages 574–583, 1996.Google Scholar
  3. 3.
    Y. Bartal. Survey on distributed paging. In Proc. of the Dagstul Workshop on On-line Algorithms, 1996.Google Scholar
  4. 4.
    R. Cypher, F. Meyer auf der Heide, C. Scheideler, and B. Vöcking. Universal algorithms for store-and-forward and wormhole routing. In Proc. of the 26th ACM Symp. on Theory of Computing (STOC), pages 356–365, 1996.Google Scholar
  5. 5.
    A. Czumaj, F. Meyer auf der Heide, and V. Stemann. Improved optimal shared memory simulations, and the power of reconfiguration. In Proc. of the 3rd Israel Symposium on Theory of Computing and Systems, pages 11–19, 1995.Google Scholar
  6. 6.
    A. Czumaj, F. Meyer auf der Heide, and V. Stemann. Shared memory simulations with triple-logarithmic delay. In Proc. of the 3rd European Symposium on Algorithms (ESA), pages 46–59, 1995.Google Scholar
  7. 7.
    A. Czumaj, F. Meyer auf der Heide, and V. Stemann. Contention resolution in hashing based shared memory simulations. Technical Report tr-rsfb-96-005, University of Paderborn, 1996.Google Scholar
  8. 8.
    M. Dietzfelbinger and F. Meyer auf der Heide. Dynamic hashing in real time. In Proc. of the 17th Annual International Colloquium on Automata, Languages and Programming, pages 6–19, 1990.Google Scholar
  9. 9.
    M. Dietzfelbinger and F. Meyer auf der Heide. Simple, efficient shared memory simulations. In Proc. of the 5th ACM Symp. on Parallel Algorithms and Architectures (SPAA), pages 110–119, 1993.Google Scholar
  10. 10.
    R. Karp, M. Luby, and F. Meyer auf der Heide. Efficient pram simulation on a distributed memory machine. Algorithmica, 16, 1996.Google Scholar
  11. 11.
    F. T. Leighton, B. M. Maggs, A. G. Ranade, and S. B. Rao. Randomized routing and sorting on fixed-connection networks. jalgo, 17:157–205, 1994.Google Scholar
  12. 12.
    C. Lund, N. Reingold, J. Westbrook, and D. Yan. On-line distributed data management. In Proc. of the 2nd European Symposium on Algorithms (ESA), 1996.Google Scholar
  13. 13.
    B. Maggs, F. Meyer auf der Heide, B. Vöcking, and M. Westermann. Exploiting locality for networks of limited bandwidth. Technical Report tr-rsfb-97-042, University of Paderborn, 1997.Google Scholar
  14. 14.
    F. Meyer auf der Heide, C. Scheideler, and V. Stemann. Exploiting storage redundancy to speed up randomized shared memory simulations. Theoretical Computer Science, 162:245–281, 1996.Google Scholar
  15. 15.
    F. Meyer auf der Heide and B. Vöcking. A packet routing protocol for arbitrary networks. In Proc. of the 12th Symp. on Theoretical Aspects of Computer Science (STACS), pages 291–302, 1995.Google Scholar
  16. 16.
    R. Ostrovsky and Y. Rabani. Universal O(congestion + dilation + log1+ε n) local control packet switching algorithms. In Proc. of the 29th ACM Symp. on Theory of Computing (STOC), to appear, 1997.Google Scholar
  17. 17.
    A. G. Ranade. How to emulate shared memory. In Proc. of the 28th IEEE Symp. on Foundations of Computer Science (FOCS), pages 185–194, 1987.Google Scholar
  18. 18.
    A. Siegel. On universal classes of fast high performance hash functions. In Proc. of the 30th IEEE Symp. on Foundations of Computer Science (FOCS), pages 20–25, 1989.Google Scholar
  19. 19.
    E. Upfal and A. Wigderson. How to share memory in a distributed system. Journal of the ACM, 34:116–127, 1987.Google Scholar
  20. 20.
    M. N. Wegman and J. L. Carter. New classes and applications of hash functions. In Proc. of the 20th IEEE Symp. on Foundations of Computer Science (FOCS), pages 175–182, 1979.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Friedhelm Meyer auf der Heide
    • 1
  • Berthold Vöcking
    • 1
  1. 1.Department of Mathematics and Computer Science and Heinz Nixdorf InstituteUniversity of PaderbornPaderbornGermany

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