A Systematic Review of Fault Management Framework in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) have progressively appeared as a buzzword for the prevalent research areas of networking in the twenty-first century. The main application areas include threat detection, industrial monitoring, environment monitoring, military surveillance, weather forecasting. Since the sensor nodes are deployed in a hostile environment, they can develop a fault due to this environmental impact. The occurrence of these faults must not hamper the functioning of the entire network. Hence, Fault Management plays a vital role in improving fault tolerance. To improve the Quality of Service (QoS) of the overall network, a fault management scheme has to be incorporated. This scheme can be further enhanced using Machine Learning. Fault Management scheme includes the fault prevention mechanism which is applied at the design level. Fault Detection is performed at the operational level using Machine Learning techniques. The classification of faults occurring in the network helps in Fault Identification and Isolation. The last step is fault recovery, which provides a suggestive countermeasure. This article discusses the taxonomy of fault management framework categorized into central, distributed, hierarchal, hybrid, classification based on their performance.