Diagnosis of Wireless Sensor Networks in Presence of Permanent and Intermittent Faults

In this paper we consider the problem of distributed fault diagnosis in Wireless Sensor Networks (WSNs). The proposed Fault Diagnosis Algorithm (FDA) aims to handle both permanent and intermittent faults. The sensor nodes with permanent communication faults can be diagnosed by using the conventional time-out mechanism. In contrast, it is difficult to detect intermittent faults due to their inherent unpredictable behavior. The FDA is based on the comparison of sensor measurements and residual energy values of neighboring sensor nodes, exploiting their spatial correlations. To handle intermittent faults, the comparisons are made for $$r$$r rounds. Two special cases of intermittent faults are considered: one, when an intermittently faulty node sends similar sensor measurement and similar residual energy value to some of its neighbors in all $$r$$r rounds; another, when it sends these values, either or both of which deviates significantly from that of some neighbors in all $$r$$r rounds. Through extensive simulation and analysis, the proposed scheme is proved to be correct, complete, and efficient to handle intermittent faults and hence, well suited for WSNs.