LiMoSense - Live monitoring in dynamic sensor networks

Abstract

We present LiMoSense, a fault-tolerant live monitoring algorithm for dynamic sensor networks. This is the first asynchronous robust average aggregation algorithm that performs live monitoring, i.e., it constantly obtains a timely and accurate picture of dynamically changing data. LiMoSense uses gossip to dynamically track and aggregate a large collection of ever-changing sensor reads. It overcomes message loss, node failures and recoveries, and dynamic network topology changes. We formally prove the correctness of LiMoSense; we use simulations to illustrate its ability to quickly react to changes of both the network topology and the sensor reads, and to provide accurate information. © 2012 Springer-Verlag.