Fast convergence of quantized consensus using Metropolis chains

Tamer Basary, Seyed Rasoul Etesami, Alex Olshevsky

Research output: Contribution to journalConference article

Abstract

We consider the quantized consensus problem on undirected connected graphs and study its expected convergence time to the set of consensus points. As compared with earlier results on the problem, we improve the convergence speed of the dynamics by a factor of n, where n is the number of agents involved in the dynamics. In particular, we show that when the edges of the network are activated based on a Poisson processes with Metropolis rates, the expected convergence time to the consensus set is at most O(n2 log n). This upper bound is better than all available results for randomized quantized consensus.

Original languageEnglish (US)
Article number7039566
Pages (from-to)1330-1334
Number of pages5
JournalProceedings of the IEEE Conference on Decision and Control
Volume2015-February
Issue numberFebruary
DOIs
StatePublished - Jan 1 2014
Event2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States
Duration: Dec 15 2014Dec 17 2014

Keywords

  • Metropolis chains
  • Quantized consensus
  • consensus convergence time

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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