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Tight Bounds for Asymptotic and Approximate Consensus

Published: 28 October 2021 Publication History
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  • Abstract

    Agreeing on a common value among a set of agents is a fundamental problem in distributed computing, which occurs in several variants: In contrast to exact consensus, approximate variants are studied in systems where exact agreement is not possible or required, e.g., in human-made distributed control systems and in the analysis of natural distributed systems, such as bird flocking and opinion dynamics.
    We study the time complexity of two classical agreement problems: non-terminating asymptotic consensus and terminating approximate consensus. Asymptotic consensus, requires agents to repeatedly set their outputs such that the outputs converge to a common value within the convex hull of initial values; approximate consensus requires agents to eventually stop setting their outputs, which must then lie within a predefined distance of each other.
    We prove tight lower bounds on the contraction ratios of asymptotic consensus algorithms subject to oblivious message adversaries, from which we deduce bounds on the time complexity of approximate consensus algorithms. In particular, the obtained bounds show optimality of asymptotic and approximate consensus algorithms presented by Charron-Bost et al. (ICALP’16) for certain systems, including the strongest oblivious message adversary in which asymptotic and approximate consensus are solvable. As a corollary we also obtain asymptotically tight bounds for asymptotic consensus in the classical asynchronous model with crashes.
    Central to the lower-bound proofs is an extended notion of valency, the set of reachable limits of an asymptotic consensus algorithm starting from a given configuration. We further relate topological properties of valencies to the solvability of exact consensus, shedding some light on the relation of these three fundamental problems in dynamic networks.

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      cover image Journal of the ACM
      Journal of the ACM  Volume 68, Issue 6
      December 2021
      283 pages
      ISSN:0004-5411
      EISSN:1557-735X
      DOI:10.1145/3484923
      Issue’s Table of Contents
      This work is licensed under a Creative Commons Attribution International 4.0 License.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 28 October 2021
      Accepted: 01 September 2021
      Revised: 01 November 2020
      Received: 01 June 2019
      Published in JACM Volume 68, Issue 6

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      Author Tags

      1. Asymptotic consensus
      2. approximate consensus
      3. dynamic networks
      4. message adversaries
      5. crash faults
      6. lower bounds

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      • Austrian Science Fund (FWF)
      • Centre National de la Recherche Scientifique (CNRS)
      • DigiCosme working group HicDiesMeus

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      • (2024)Semantic and Context Understanding for Sentiment Analysis in Hindi Handwritten Character Recognition Using a Multiresolution TechniqueACM Transactions on Asian and Low-Resource Language Information Processing10.1145/355789523:1(1-22)Online publication date: 15-Jan-2024
      • (2024)Iterative approximate Byzantine consensus in arbitrary directed graphsDistributed Computing10.1007/s00446-024-00468-2Online publication date: 22-May-2024
      • (2022)Optimal Synchronous Approximate Agreement with Asynchronous FallbackProceedings of the 2022 ACM Symposium on Principles of Distributed Computing10.1145/3519270.3538442(70-80)Online publication date: 20-Jul-2022

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