Fast Convergence for Consensus in Dynamic Networks

  • T-H. Hubert Chan
  • Li Ning
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6756)


We study the convergence time required to achieve consensus in dynamic networks. In each time step, a node’s value is updated to some weighted average of its neighbors’ and its old values. We study the case when the underlying network is dynamic, and investigate different averaging models. Both our analysis and experiments show that dynamic networks exhibit fast convergence behavior, even under very mild connectivity assumptions.


Transition Matrix Dynamic Network Fast Convergence Convergence Time Transition Matrice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • T-H. Hubert Chan
    • 1
  • Li Ning
    • 1
  1. 1.The University of Hong KongHong Kong

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