Abstract
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. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Chan, T. H. H., & Ning, L. (2011). Fast convergence for consensus in dynamic networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6756 LNCS, pp. 514–525). https://doi.org/10.1007/978-3-642-22012-8_41
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