• Media type: E-Article; Text; Electronic Conference Proceeding
  • Title: Fast, Robust, Quantizable Approximate Consensus
  • Contributor: Charron-Bost, Bernadette [Author]; Függer, Matthias [Author]; Nowak, Thomas [Author]
  • imprint: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2016
  • Language: English
  • DOI: https://doi.org/10.4230/LIPIcs.ICALP.2016.137
  • Keywords: dynamic networks ; averaging algorithms ; approximate consensus
  • Origination:
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  • Description: We introduce a new class of distributed algorithms for the approximate consensus problem in dynamic rooted networks, which we call amortized averaging algorithms. They are deduced from ordinary averaging algorithms by adding a value-gathering phase before each value update. This results in a drastic drop in decision times, from being exponential in the number n of processes to being polynomial under the assumption that each process knows n. In particular, the amortized midpoint algorithm is the first algorithm that achieves a linear decision time in dynamic rooted networks with an optimal contraction rate of 1/2 at each update step. We then show robustness of the amortized midpoint algorithm under violation of network assumptions: it gracefully degrades if communication graphs from time to time are non rooted, or under a wrong estimate of the number of processes. Finally, we prove that the amortized midpoint algorithm behaves well if processes can store and send only quantized values, rendering it well-suited for the design of dynamic networked systems. As a corollary we obtain that the 2-set consensus problem is solvable in linear time in any dynamic rooted network model.
  • Access State: Open Access