A Fault Detection Algorithm Based on Cluster Analysis in Wireless Sensor Networks

In this paper, we present a distributed fault detection algorithm based on k-means clustering for WSN. The nodes within a cluster are divided into three sub-clustering according to their measurements´ similarity. We conclude the sensor nodes´ working state from the N recent states of sub-clustering, so as to detect, locate, and get rid of the fault nodes. Simulation results show that the k-means cluster fault detection algorithm has a better performance than the distributed Bayesian algorithms. Moreover, the computational complexity of the proposed algorithm is low.