Towards Self-Healing in Wireless Sensor Networks

Abstract

Faults in WSN are very common and appear in different levels of the system. For pervasive applications to be adopted by end-users there is a need for autonomic self-healing. This paper discusses our initial approach to self-healing in WSN and describes experiments with two case studies of body sensor deployment. We evaluate the impact of sensor faults on activity and gesture classification accuracy respectively and develop mechanisms that will allow detection of those faults during system’s operation.