Scalable Distributed Diagnosis Algorithm for Wireless Sensor Networks

Abstract

This paper investigates the distributed self diagnosis problem for wireless sensor networks (WSN). One of the fundamental algorithm design issue for WSN is conservation of energy at each sensor node. A heartbeat comparison based diagnosis model is proposed, which is shown to be energy efficient. Analytical studies and simulation results show that the performance of proposed algorithm is comparable to that of the existing known algorithms in both delay and message count prospective. At the same time, the per-node message overhead is substantially reduced and becomes scalable.