Fault Detection Algorithm using Clustering in WSN

Wireless sensor networks have been established, at an early stage in their development, to be a useful dimension technology for environmental monitoring applications. Wireless sensor nodes may experience two types of faults that would lead to the degradation of performance. One type is function fault, which normally results in the crash of individual nodes, packet failure, routing failure or network separation. In this paper, the problem of adaptive Distributed diagnosis in WSN using clustering is measured.. In fact, fault-diagnosis becomes an important building block to establish dependability in WSN. An important problem in WSN is the distributed system-level diagnosis problem whose purpose is to have each fault-free sensor node to determine the state of all the sensor nodes in the structure. The parameters such as diagnostic latency and message complexity are used for evaluating the performance of proposed diagnosis algorithm. After the complete diagnosis global diagnostic information is provided to have a consistent diagnosis view of the network .The threshold value tells how much percentage of nodes are faulty or fault-free. Diagnosis algorithm should be efficient enough to find the status (either faulty or fault free) of each sensor node in the network.