• DocumentCode
    3536797
  • Title

    Convergence time for unbiased quantized consensus

  • Author

    Etesami, Seyed Rasoul ; Basar, Tamer

  • Author_Institution
    Coordinated Sci. Lab., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2013
  • fDate
    10-13 Dec. 2013
  • Firstpage
    6190
  • Lastpage
    6195
  • Abstract
    We revisit the quantized consensus problem on undirected connected graphs, and obtain some strong results on expected time to convergence. This is unbiased consensus, because the edges emanating from a node have equal probability of being selected. The paper first develops an approach that bounds the expected convergence time of the underlying discrete-time dynamics. The bounds are tight for some simple networks when there exists some symmetry in the network. Following this, the paper provides a tight expression for the expected convergence time of unbiased quantized consensus over general networks. Finally, the paper shows that the expected convergence time can be expressed in terms of the effective resistances of the associated Cartesian product graph. The approach adopted in the paper uses the theory of harmonic functions for reversible Markov chains.
  • Keywords
    Markov processes; convergence; graph theory; network theory (graphs); probability; associated Cartesian product graph; discrete-time dynamics; equal probability; expected convergence time; general networks; harmonic function theory; reversible Markov chains; unbiased quantized consensus problem; undirected connected graphs; Convergence; Educational institutions; Harmonic analysis; Markov processes; Resistance; Upper bound; Markov chains; Quantized consensus; convergence time; random walk; social networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
  • Conference_Location
    Firenze
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-5714-2
  • Type

    conf

  • DOI
    10.1109/CDC.2013.6760867
  • Filename
    6760867