Title
Eavesdropping-Based Gossip Algorithms for Distributed Consensus in Wireless Sensor Networks
Abstract
In this letter, we present an eavesdropping-based gossip algorithm (EBGA). In the novel algorithm, when a node unicasts its values to a randomly selected neighboring node, all other nodes, which eavesdrop these values, simultaneously update their state values. By exploiting the broadcast nature of wireless communications, this novel algorithm has similar performance to broadcast gossip algorithms. Although broadcast gossip algorithms have the fastest rate of convergence among all gossip algorithms, they either converge to a random value rather than the average consensus, or need out-degree information available for each node to guarantee convergence to the average consensus. Utilizing non-negative matrix theory and ergodicity coefficient, we have proved that this novel algorithm can converge to the average consensus without any assumption which is difficult to be realized in real networks.
Year
DOI
Venue
2015
10.1109/LSP.2015.2398191
IEEE Signal Process. Lett.
Keywords
Field
DocType
nonnegative matrix theory,distributed averaging,wireless communications,distributed consensus,eavesdropping-based gossip algorithms,broadcast gossip algorithms,distributed signal processing,matrix algebra,random value,broadcast communication,ebga,randomly selected neighboring node,ergodicity coefficient,wireless sensor networks,out-degree information,artificial neural networks,convergence,vectors,acceleration,materials
Convergence (routing),Consensus,Broadcasting,Ergodicity,Wireless,Eavesdropping,Computer science,Computer network,Theoretical computer science,Rate of convergence,Wireless sensor network
Journal
Volume
Issue
ISSN
22
9
1070-9908
Citations 
PageRank 
References 
1
0.36
7
Authors
4
Name
Order
Citations
PageRank
Shaochuan Wu1186.51
Bo Liu210.36
Xu Bai3379.94
Yuguan Hou422.40