An Adaptive Approach to Discriminate the Persistence of Faults in Wireless Sensor Networks

This paper presents a parametric fault detection algorithm which can discriminate the persistence (permanent, intermittent, and transient) of faults in wireless sensor networks. The main characteristics of these faults are the amount the fault appears. We adopt this state-holding time to discriminate transient from intermittent faults. Neighbor-coordination-based approach is adopted, where faulty sensor nodes are detected based on comparisons between neighboring nodes and dissemination of the decision made at each node. Simulation results demonstrate the robustness of the work at varying transient fault rate. 1. Introduction Node failures and environmental hazards cause frequent topology change, communication failure, and network partition. Such perturbations are far more common in wireless sensor networks (WSNs) than those found in traditional wireless networks. The extent of such a perturbations depends on the persistence of faults. Based on persistence, faults can be classified as transient, intermittent, or permanent. A transient fault will eventually disappear without any apparent intervention, whereas a permanent one will remain unless it is removed by some external agency [1]. After their first appearance, the rate of fault appearance is relatively high for intermittent faults, and finally the intermittent faulty nodes tend to become permanent [2, 3]. Permanent or hard faults are software or hardware faults that always produce errors when they are fully exercised [4]. In fact, experimental studies have shown that more than of the faults that occur in real systems are transient or intermittent faults [3, 5, 6]. These faults are more severe, from both data aggregation and network lifetime perspective. They are much problematic to diagnose and handle. In contrast, permanent faults are considerably easier to diagnose and handle. Since the effect of faults is not always present, detection of intermittent or transient faults requires repetitive testing at the discrete time in contrast to single test to detect permanent faults. Discrimination of transient from intermittent or permanent faults is crucial as a sensor node with transient fault does not necessarily imply that the sensor node should be isolated although the unstable environment might warrant a temporary shutdown [4]. A discrimination between transient and intermittent or permanent faults solves the following key problems. Effective Bandwidth Utilization By isolating permanent faults, the traffic generated by the permanent faulty nodes is restricted. Effective Energy Utilization The depletion