Fault Diagnosis in Wireless Sensor Network using Self/Non-self Discrimination Principle

Abstract

The fault diagnosis in wireless sensor networks (WSNs) is one of the most important topic in recent years as a lot of research work havealready been done in this area. The problem of fault diagnosis in WSN can be resembled with artificial immune system (AIS) in many different ways. In this paper, a self/non-self discrimination algorithm (SNSD) has been proposed to identify faulty sensor nodes in wireless sensor network (WSN). The performance metrics such as detection accuracy (DA), false alarm rate (FAR) and false positive rate (FPR) are used to evaluate the performance of the proposed algorithm. The simulation results show that the SNSD algorithm gives better result in terms of performance metrics compared to the existing algorithms.