Self-Organized Fault-Tolerant Feature Extraction in Distributed Wireless Sensor Networks ∗
@inproceedings{Krishnamachari2002SelfOrganizedFF, title={Self-Organized Fault-Tolerant Feature Extraction in Distributed Wireless Sensor Networks ∗}, author={Bhaskar Krishnamachari}, year={2002} }
We propose a distributed solution for a canonical task in wireless sensor networks – the extraction of information about interesting environmental features. 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% of faults can be corrected using this algorithm even when as many as 10% of the nodes are faulty.
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