Randomized Consensus in Expected O(n2) Total Work Using Single-Writer Registers

  • James Aspnes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6950)


A new weak shared coin protocol yields a randomized wait-free shared-memory consensus protocol that uses an optimal O(n 2) expected total work with single-writer registers despite asynchrony and process crashes. Previously, no protocol was known that achieved this bound without using multi-writer registers.


Total Work Constant Probability Consensus Protocol Total Vote Adversary Strategy 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abrahamson, K.: On achieving consensus using a shared memory. In: Proceedings of the 7th Annual ACM Symposium on Principles of Distributed Computing (PODC), pp. 291–302 (1988)Google Scholar
  2. 2.
    Alon, N., Spencer, J.H.: The Probabilistic Method. John Wiley & Sons, Chichester (1992)zbMATHGoogle Scholar
  3. 3.
    Aspnes, J.: Time- and space-efficient randomized consensus. Journal of Algorithms 14(3), 414–431 (1993)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Aspnes, J., Censor, K.: Approximate shared-memory counting despite a strong adversary. In: SODA 2009: Proceedings of the Nineteenth Annual ACM -SIAM Symposium on Discrete Algorithms, pp. 441–450. Society for Industrial and Applied Mathematics, Philadelphia (2009)CrossRefGoogle Scholar
  5. 5.
    Aspnes, J., Herlihy, M.: Fast randomized consensus using shared memory. Journal of Algorithms 11(3), 441–461 (1990)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Aspnes, J., Waarts, O.: Randomized consensus in expected O(N log2 N) operations per processor. SIAM Journal on Computing 25(5), 1024–1044 (1996)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Attiya, H., Censor, K.: Tight bounds for asynchronous randomized consensus. Journal of the ACM 55(5), 20 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Attiya, H., Dolev, D., Shavit, N.: Bounded polynomial randomized consensus. In: Proceedings of the Eighth Annual ACM Symposium on Principles of Distributed Computing, Edmonton, Alberta, Canada, August 14–16, pp. 281–293 (1989)Google Scholar
  9. 9.
    Attiya, H., Welch, J.: Distributed Computing: Fundamentals, Simulations, and Advanced Topics, 2nd edn. John Wiley & Sons, Chichester (2004)CrossRefzbMATHGoogle Scholar
  10. 10.
    Azuma, K.: Weighted sums of certain dependent random variables. Tôhoku Mathematical Journal 19(3), 357–367 (1967)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Bracha, G., Rachman, O.: Approximated counters and randomized consensus. Technical Report 662, Technion (1990)Google Scholar
  12. 12.
    Bracha, G., Rachman, O.: Randomized consensus in expected O(n 2 logn) operations. In: Toueg, S., Spirakis, P.G., Kirousis, L.M. (eds.) WDAG 1991. LNCS, vol. 579, pp. 143–150. Springer, Heidelberg (1992)CrossRefGoogle Scholar
  13. 13.
    Chor, B., Israeli, A., Li, M.: Wait-free consensus using asynchronous hardware. SIAM J. Comput. 23(4), 701–712 (1994)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Dwork, C., Herlihy, M., Plotkin, S., Waarts, O.: Time-lapse snapshots. SIAM Journal on Computing 28(5), 1848–1874 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Grimmett, G.R., Stirzaker, D.R.: Probability and Random Processes. Oxford University Press, Oxford (2001)zbMATHGoogle Scholar
  16. 16.
    Mitzenmacher, M., Upfal, E.: Probability and Computing: Randomized Algorithms and Probabilistic Analysis. Cambridge University Press, Cambridge (2005)CrossRefzbMATHGoogle Scholar
  17. 17.
    Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge University Press, Cambridge (1995)CrossRefzbMATHGoogle Scholar
  18. 18.
    Saks, M., Shavit, N., Woll, H.: Optimal time randomized consensus—making resilient algorithms fast in practice. In: Proceedings of the 2nd Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 351–362 (1991)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • James Aspnes
    • 1
  1. 1.Yale UniversityUSA

Personalised recommendations