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Quick atomic broadcast

Extended abstract
  • Piotr Berman
  • Anupam A. Bharali
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 725)

Abstract

In Atomic Broadcast protocols, the participating processors may initiate the broadcast of a message at any time; the goal is to make all non-faulty processors deliver the same set of messages in the same order. Our objective in this paper is to assure that the delivery time (from the moment of initiation of a message to its last delivery by a correct processor) is proportional to the actual number of faults in a given run of the protocol. We study this problem in synchronous systems and two models of semi-synchronous systems in presence of various classes of processor failures.

We offer a technique that allows to convert “early stopping” Distributed Consensus protocols to Atomic Broadcast protocols with the above property. The resulting Atomic Broadcast protocols are faster and use smaller messages than the protocols proposed so far.

Keywords

Delivery Time Timing Uncertainty Synchronous System Byzantine Agreement Crash Failure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [ADLS 91]
    H. Attiya, C. Dwork, N. Lynch and L. Stockmeyer, “Bounds on the Time to Reach Agreement in the Presence of Timing Uncertainty”, ACM Symp. on Theory of Computing, May 1991, pp. 359–369. Also in Technical Memo TM-4-35, Laboratory for Computer Science, MIT and IBM Research Report RJ7853.Google Scholar
  2. [BB1 92]
    P. Berman and A.A. Bharali “Distributed Consensus in a Semi-synchronous System”, 6th IEEE International Parallel Processing Symp., March 1992.Google Scholar
  3. [BB2 92]
    P. Berman and A.A. Bharali “Quick Atomic Broadcast”, Tech Report CS-92-16, Dept. of Computer Science, Penn State University, May 1992.Google Scholar
  4. [BB3 92]
    P. Berman and A.A. Bharali “Asynchronous Atomic Broadcast”, Tech Report CS-92-28, Dept. of Computer Science, Penn State University, December 1992.Google Scholar
  5. [BB 93]
    A.A. Bharali and P. Berman “Distributed Consensus with General Omission Failures and Timing Uncertainty”, 12th IEEE International Phoenix Conf. on Computers and Communications, March 1993.Google Scholar
  6. [BE 90]
    M. Ben-Or and R. El-Yaniv “Interactive Consistency in Constant Time”, manuscript, 1990. Submitted for publication.Google Scholar
  7. [BG 92]
    P. Berman and J.A. Garay “Optimal Early-Stopping in Distributed Consensus”, 6th International Workshop on Distributed Algorithm, 1992, pp. 221–237.Google Scholar
  8. [BGT 90]
    N. Budhiraja, A. Gopal and S. Toueg “Early-Stopping Distributed Bidding and Applications”, 4th International Workshop on Distributed Algorithm, 1990, pp. 304–320.Google Scholar
  9. [BSS 91]
    K. Birman, A. Schiper and P. Stephenson “Lightweight Causal and Atomic Group Multicast”, ACM Transactions on Computer Systems, Vol 9, No. 3, 1991, pp. 272–314.Google Scholar
  10. [CASD 85]
    F. Cristian, H. Aghili, H.R. Strong and D. Dolev “Atomic Broadcast: From Simple Message Diffusion to Byzantine Agreement”, Fifth International Symp. on Fault-Tolerant Computing, 1985, pp. 200–206. Revised in IBM Research Report, February 1991.Google Scholar
  11. [CDS 90]
    F. Cristian, D. Dolev and H.R. Strong “New Latency bounds for Atomic Broadcast”, 11th IEEE Real-Time Systems Symposium, 1990, pp. 156–165.Google Scholar
  12. [DDS 87]
    D. Dolev, C. Dwork and L. Stockmeyer “On the Minimal Synchronization needed for Distributed Consensus”, Journal of the ACM, Vol 34, No. 1, 1987, pp. 77–97.Google Scholar
  13. [DLS 88]
    C. Dwork, N. Lynch and L. Stockmeyer “Consensus in the Presence of Partial Synchrony”, Journal of the ACM, Vol 35, 1988, pp. 288–323.Google Scholar
  14. [DM 90]
    C. Dwork and Y. Moses “Knowledge and Common Knowledge in a Byzantine environment: Crash Failures”, Information and Computation, Vol 88, No. 2, October 1990, pp. 156–186.Google Scholar
  15. [DRS 82]
    D. Dolev, R. Reischuk and H.R. Strong “Eventual is Earlier than Immediate”, 23rd IEEE Symp. on Foundations of Computer Science, 1982, pp. 196–203. Journal version in “Early Stopping in Byzantine Agreement”, Journal of the ACM, Vol 37, October 1990, pp. 720–741.Google Scholar
  16. [FLP 85]
    M. Fischer, N. Lynch and M. Paterson “Impossibility of Distributed Consensus with One Faulty Processor”, Journal of the ACM, Vol 32, No. 2, 1985, pp. 374–382.Google Scholar
  17. [FM 88]
    P. Feldman and S. Micali “Optimal Algorithms for Byzantine Agreement”, ACM Symp. on Theory of Computing, 1988, pp. 148–161. Also in P. Feldman Ph.D. Thesis, MIT, 1988.Google Scholar
  18. [G 92]
    A. Gopal “Fault Tolerant Broadcasts and Multicasts: The Problem of Inconsistency and Contamination”, Ph.D. Thesis, Cornell, 1992.Google Scholar
  19. [GSTC 90]
    A. Gopal, R. Strong, S. Toueg and F. Cristian “Early-Delivery Atomic Broadcast”, 9th ACM Symp. on Principles of Distributed Computing, 1990, pp. 297–309.Google Scholar
  20. [P 91]
    S. Ponzio “Consensus in the Presence of Timing Uncertainty: Omission and Byzantine Failures”, 10th ACM Symp. on Principles of Distributed Computing, August 1991, pp. 125–138.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1993

Authors and Affiliations

  • Piotr Berman
    • 1
  • Anupam A. Bharali
    • 1
  1. 1.Department of Computer Science and EngineeringThe Pennsylvania State UniversityUniversity ParkUSA

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