An improved distributed Bayesian algorithm for fault-tolerant detection in electromagnetic spectrum monitoring sensor networks

Electromagnetic spectrum monitoring sensor networks (ESMSNs) have become a new distributed solution for the electromagnetic spectrum monitoring and attracted a large scholars´ attention due to its better detection performance. However, the detection performance of ESMSNs will decrease rapidly when the faults occur to the monitoring sensor nodes, which result from the node device itself and the harsh or hostile environment where they are deployed. The distributed Bayesian algorithm was proposed to correct some errors resulted from the sensor faults. But new errors were introduced while correcting errors. Therefore, it is necessary to do some further research on the distributed fault-tolerant detection for ESMSNs. We propose an improved distributed Bayesian algorithm for fault-tolerant detection in ESMSNs and investigate the performance of detecting and correcting such faults. Analysis and Simulation results show the proposed algorithm can perform better than the distributed Bayesian algorithm and the proposed algorithm can still obtain higher reduction in the average number of errors when the probability of the monitoring sensor node fault is high.