Distributed Intermittent Fault Diagnosis in Wireless Sensor Networks Using Clustering

Wireless sensor networks (WSNs) are an important tool for monitoring distributed remote environments. Faults occurring to sensor nodes are common due to the sensor device itself and the harsh environment where the sensor nodes are deployed. It is well known that the distributed fault detection (DFD)scheme checks out the failed nodes by exchanging data and mutually testing among neighbor nodes in this network. But the fault detection accuracy of aDFD scheme would decrease rapidly when the number of neighbor nodes to be diagnosed is small and the node´s failure ratio is high. In this paper, aDFD scheme using clustering is proposed which satisfies three important diagnosis properties such as consistency, completeness and accuracy. These properties have been also proved. Simulation results demonstrate that the proposed DFD scheme increases the fault detection accuracy in comparison with a DFD scheme without clustering.