Advertisement

How to Solve Consensus in the Smallest Window of Synchrony

  • Dan Alistarh
  • Seth Gilbert
  • Rachid Guerraoui
  • Corentin Travers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5218)

Abstract

This paper addresses the following question: what is the minimum-sized synchronous window needed to solve consensus in an otherwise asynchronous system? In answer to this question, we present the first optimally-resilient algorithm ASAP that solves consensus as soon as possible in an eventually synchronous system, i.e., a system that from some time GST onwards, delivers messages in a timely fashion. ASAP guarantees that, in an execution with at most f failures, every process decides no later than round GST + f + 2, which is optimal.

Keywords

Correct Process Failure Detector Small Window Minimum Estimate Previous Round 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Boichat, R., Dutta, P., Frolund, S., Guerraoui, R.: Deconstructing paxos. SIGACT News 34(1), 47–67 (2003)CrossRefGoogle Scholar
  2. 2.
    Boichat, R., Dutta, P., Frolund, S., Guerraoui, R.: Reconstructing paxos. SIGACT News 34(2), 42–57 (2003)CrossRefGoogle Scholar
  3. 3.
    Chandra, T., Hadzilacos, V., Toueg, S.: The weakest failure detector for solving consensus. J. ACM 43(4), 685–722 (1996)zbMATHCrossRefMathSciNetGoogle Scholar
  4. 4.
    Chandra, T., Toueg, S.: Unreliable failure detectors for reliable distributed systems. J. ACM 43(2), 225–267 (1996)zbMATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Dolev, D., Reischuk, R., Strong, H.R.: Early stopping in byzantine agreement. J. ACM 37(4), 720–741 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Dutta, P., Guerraoui, R.: The inherent price of indulgence. In: PODC, pp. 88–97 (2002)Google Scholar
  7. 7.
    Dutta, P., Guerraoui, R.: The inherent price of indulgence. Distributed Computing 18(1), 85–98 (2005)CrossRefGoogle Scholar
  8. 8.
    Dutta, P., Guerraoui, R., Keidar, I.: The overhead of consensus failure recovery. Distributed Computing 19(5-6), 373–386 (2007)CrossRefGoogle Scholar
  9. 9.
    Dutta, P., Guerraoui, R., Lamport, L.: How fast can eventual synchrony lead to consensus? In: DSN, pp. 22–27 (2005)Google Scholar
  10. 10.
    Dwork, C., Lynch, N., Stockmeyer, L.: Consensus in the presence of partial synchrony. J. ACM 35(2), 288–323 (1988)CrossRefMathSciNetGoogle Scholar
  11. 11.
    Fisher, M., Lynch, N., Paterson, M.: Impossibility of distributed consensus with one faulty process. J. ACM 32(2), 374–382 (1985)CrossRefGoogle Scholar
  12. 12.
    Gafni, E.: Round-by-round fault detectors: Unifying synchrony and asynchrony (extended abstract). In: PODC, pp. 143–152 (1998)Google Scholar
  13. 13.
    Guerraoui, R.: Indulgent algorithms (preliminary version). In: PODC, pp. 289–297 (2000)Google Scholar
  14. 14.
    Guerraoui, R., Raynal, M.: The information structure of indulgent consensus. IEEE Transactions on Computers 53(4), 453–466 (2004)CrossRefGoogle Scholar
  15. 15.
    Halpern, J.Y., Moses, Y.: Knowledge and common knowledge in a distributed environment. J. ACM 37(3), 549–587 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  16. 16.
    Keidar, I., Rajsbaum, S.: On the cost of fault-tolerant consensus when there are no faults (preliminary version). SIGACT News 32(2), 45–63 (2001)CrossRefGoogle Scholar
  17. 17.
    Keidar, I., Shraer, A.: Timeliness, failure-detectors, and consensus performance. In: PODC, pp. 169–178 (2006)Google Scholar
  18. 18.
    Keidar, I., Shraer, A.: How to choose a timing model? In: DSN, pp. 389–398 (2007)Google Scholar
  19. 19.
    Lamport, L.: Generalized consensus and paxos. Microsoft Research Technical Report MSR-TR-2005-33 (March 2005)Google Scholar
  20. 20.
    Lamport, L.: Lower bounds for asynchronous consensus. Distributed Computing 19(2), 104–125 (2006)CrossRefMathSciNetGoogle Scholar
  21. 21.
    Lamport, L., Fisher, M.: Byzantine generals and transaction commit protocols (unpublished) (April 1982)Google Scholar
  22. 22.
    Lamport, L., Shostak, R., Pease, M.: The byzantine generals problem. ACM Trans. Program. Lang. Syst. 4(3), 382–401 (1982)zbMATHCrossRefGoogle Scholar
  23. 23.
    Lamport, L.: Fast paxos. Distributed Computing 19(2), 79–103 (2006)CrossRefMathSciNetGoogle Scholar
  24. 24.
    Lynch, N.: Distributed Algorithms. Morgan Kaufmann, San Francisco (1996)zbMATHGoogle Scholar
  25. 25.
    Pease, M., Shostak, R., Lamport, L.: Reaching agreement in the presence of faults. J. ACM 27(2), 228–234 (1980)zbMATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Dan Alistarh
    • 1
  • Seth Gilbert
    • 1
  • Rachid Guerraoui
    • 1
  • Corentin Travers
    • 2
  1. 1.EPFL LPDLausanneSwitzerland
  2. 2.Universidad Politecnica de MadridMadridSpain

Personalised recommendations