Optimal amortized distributed consensus

  • Amotz Bar-Noy
  • Xiaotie Deng
  • Juan A. Garay
  • Tiko Kameda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 579)


Are randomized consensus algorithms more powerful than deterministic ones? Seemingly so, since randomized algorithms exist that reach consensus in expected constant number of rounds, whereas the deterministic counterparts are constrained by the rt + 1 lower bound in the number of communication rounds, where t is the maximum number of faults to be tolerated.

In this paper, however, we study the behavior of deterministic algorithms when consensus is repeatedly needed, say k times. We show that it is possible to achieve consensus with the optimal number of processors (n > 3t), and optimal amortized cost in all other measures: the number of communication rounds r*, the maximal message size m*, and the total bit complexity b*.

More specifically, we achieve the following amortized bounds for k consensus instances: r*=O(1 + t/k), b*=O(t2+ t1/k), and m*=O(1 + t2/k). When k ≥ t2, then r* and m* are O(1) and b*=O(t2) which is optimal.


Message Size Consensus Problem Consensus Algorithm Communication Round Byzantine Agreement 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Amotz Bar-Noy
    • 2
  • Xiaotie Deng
    • 2
  • Juan A. Garay
    • 1
  • Tiko Kameda
    • 3
  1. 1.IBM T. J. Watson Research CenterYorktown Heights
  2. 2.Department of Computer ScienceYork UniversityNorth YorkCanada
  3. 3.School of Computing ScienceSimon Fraser UniversityBurnabyCanada

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