Gossip algorithms are attractive for in-network processing in sensor networksbecause they do not require any specialized routing, there is no bottleneck orsingle point of failure, and they are robust to unreliable wireless networkconditions. Recently, there has been a surge of activity in the computerscience, control, signal processing, and information theory communities,developing faster and more robust gossip algorithms and deriving theoreticalperformance guarantees. This article presents an overview of recent work in thearea. We describe convergence rate results, which are related to the number oftransmitted messages and thus the amount of energy consumed in the network forgossiping. We discuss issues related to gossiping over wireless links,including the effects of quantization and noise, and we illustrate the use ofgossip algorithms for canonical signal processing tasks including distributedestimation, source localization, and compression.
translated by 谷歌翻译