A Fault-Tolerant Event Boundary Detection Algorithm in Sensor Networks

This paper targets the detection of the reach of events in sensor networks with faulty sensors. Typical applications include the detection of the transportation front line of a contamination and estimation of the region in forest fire. We propose an algorithm for detection the boundary of such events. Our algorithm is purely localized and thus is suitable for large scale of sensor networks. The computational overhead is low since the detection algorithm is based on a simple clustering technique which only simple numerical operations are involved. Simulation results show that our algorithm can clearly detect the event boundary when as many as 20% sensors become faulty. Therefore, our algorithm achieves a great improvement over the previous algorithms. In addition, our proposed detection algorithm can accept any kind of scalar values as inputs. It can be applied as long as the "events" can be modeled by numerical numbers.