Distributed Bayesian algorithms for fault-tolerant event region detection in wireless sensor networks

We propose a distributed solution for a canonical task in wireless sensor networks-the binary detection of interesting environmental events. We explicitly take into account the possibility of sensor measurement faults and develop a distributed Bayesian algorithm for detecting and correcting such faults. Theoretical analysis and simulation results show that 85-95 percent of faults can be corrected using this algorithm, even when as many as 10 percent of the nodes are faulty.