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
Link To Document :
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