Cluster-based distributed consensus

Author

Li, Wenjun ; Dai, Huaiyu

Author_Institution

Qualcomm Inc, San Diego, CA

Volume

8

Issue

1

fYear

2009

Firstpage

28

Lastpage

31

Abstract

In this paper, we incorporate clustering techniques into distributed consensus algorithms for faster convergence and better energy efficiency. Together with a simple distributed clustering algorithm, we design cluster-based distributed consensus algorithms in forms of both fixed linear iteration and randomized gossip. The time complexity of the proposed algorithms is presented in terms of metrics of the original and induced graphs, through which the advantage of clustering is revealed. Our cluster-based algorithms are also shown to achieve an Omega(log n) gain in message complexity over the standard ones.

Keywords

communication complexity; convergence; distributed algorithms; iterative methods; pattern clustering; wireless sensor networks; cluster-based distributed consensus; distributed clustering algorithm; distributed consensus algorithms; energy efficiency; fixed linear iteration; message complexity; time complexity; wireless sensor networks; Algorithm design and analysis; Broadcasting; Clustering algorithms; Convergence; Distributed algorithms; Distributed computing; Energy efficiency; Helium; Iterative algorithms; Robustness; Clustering; distributed computing; distributed consensus; sensor networks;

fLanguage

English

Journal_Title

Wireless Communications, IEEE Transactions on

Publisher

ieee

ISSN

1536-1276

Type

jour

DOI

10.1109/T-WC.2009.071146

Filename

4786475