• DocumentCode
    18370
  • Title

    Degree Fluctuations and the Convergence Time of Consensus Algorithms

  • Author

    Olshevsky, Alex ; Tsitsiklis, John N.

  • Author_Institution
    Dept. of Ind. & Enterprise Syst. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • Volume
    58
  • Issue
    10
  • fYear
    2013
  • fDate
    Oct. 2013
  • Firstpage
    2626
  • Lastpage
    2631
  • Abstract
    We consider a consensus algorithm in which every node in a sequence of undirected, B-connected graphs assigns equal weight to each of its neighbors. Under the assumption that the degree of each node is fixed (except for times when the node has no connections to other nodes), we show that consensus is achieved within a given accuracy ε on n nodes in time B+4n3 Bln(2n/ε). Because there is a direct relation between consensus algorithms in time-varying environments and in homogeneous random walks, our result also translates into a general statement on such random walks. Moreover, we give a simple proof of a result of Cao, Spielman, and Morse that the worst case convergence time becomes exponentially large in the number of nodes n under slight relaxation of the degree constancy assumption.
  • Keywords
    distributed control; graph theory; random processes; time-varying systems; B-connected graphs; consensus algorithms; convergence time; degree constancy assumption; degree fluctuations; homogeneous random walks; time-varying environments; undirected graphs; worst case convergence time; Algorithm design and analysis; Convergence; Markov processes; Networked control systems; Polynomials; Upper bound; Vectors; Consensus protocols; Markov chains; distributed control;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2013.2257969
  • Filename
    6497513