An Upper Bound on the Convergence Time for Quantized Consensus of Arbitrary Static Graphs

Shang Shang, Paul Cuff, Pan Hui, Sanjeev Kulkarni

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


We analyze a class of distributed quantized consensus algorithms for arbitrary static networks. In the initial setting, each node in the network has an integer value. Nodes exchange their current estimate of the mean value in the network, and then update their estimation by communicating with their neighbors in a limited capacity channel in an asynchronous clock setting. Eventually, all nodes reach consensus with quantized precision. We analyze the expected convergence time for the general quantized consensus algorithm proposed by Kashyap et al. ("Quantized consensus," Automatica, 2007). We use the theory of electric networks, random walks, and couplings of Markov chains to derive an O(N3 log N) upper bound for the expected convergence time on an arbitrary graph of size N, improving on the state of art bound of O(N5) for quantized consensus algorithms. Our result is not dependent on graph topology. Example of complete graphs is given to show how to extend the analysis to graphs of given topology. This is consistent with the analysis in "Convergence speed of binary interval consensus," (M. Draief and M. Vojnovic, SIAM J. Control and Optimization, 2012.

Original languageEnglish (US)
Article number6862838
Pages (from-to)1127-1132
Number of pages6
JournalIEEE Transactions on Automatic Control
Issue number4
StatePublished - Apr 1 2015

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


  • Convergence time
  • distributed quantized consensus
  • gossip


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