Faulty Sensor Node Detection Using Round Trip Time and Discrete Paths in WSNs

Wireless sensor networks (WSNs) with efficient and accurate design to increase the quality of service (QoS) have become a hot area of research. Implementing the efficient and accurate WSNs requires deployment of the large numbers of portable sensor nodes in the field. The quality of service of such networks is affected by lifetime and failure of sensor node. In order to improve the quality of service, the data from faulty sensor nodes has to be ignored or discarded in the decision-making process. Hence, detection of faulty sensor node is of prime importance. In the proposed method, discrete round trip paths (RTPs) are compared on the basis of round trip delay (RTD) time to detect the faulty sensor node. RTD protocol is implemented in NS2 software. WSNs with circular topology are simulated to determine the RTD time of discrete RTPs. Scalability of the proposed method is verified by simulating the WSNs with various sensor nodes. 1. Introduction Wireless sensor networks (WSNs) consist of portable sensor nodes distributed in the field according to the requirement of specific application. WSNs with large numbers of sensor nodes found applications in the area of environmental monitoring, military operations, smart homes, surveillance, industries, and hospitals [1, 2]. In most of the applications, portable sensor nodes are placed randomly. If a sensor node deployed in the field becomes faulty, dead, or malfunction, then the resultant processed value will deviate from the mean and can lead to inaccurate analysis [3, 4]. Sensor node in the field can become faulty due to various reasons such as battery failure, hardware or software failure, and wireless device problem. Lifetime of WSNs is affected due to failure in portable sensor nodes [5, 6]. This will degrade the quality of service (QoS) of WSNs. Hence, fault detection becomes a critical issue in WSNs. Designing the efficient fault detection method to reduce the detection time as well as energy consumed by sensor node during fault detection is a need of time. Faulty sensor nodes in WSNs can be neglected or discarded during the decision making to achieve the accuracy in detection [7, 8]. Jiang [9] has suggested the fault detection based on neighbor nodes data analysis. In this method, fault detection accuracy will decrease rapidly if the numbers of neighbor nodes to be diagnosed are small and the node’s failure ratio is high. Confidence factor measurement based neighbor data analysis proposed by Zhipeng et al. [10] to detect the faulty node has limitations due to the weak and inaccurate algorithm. In [11], link