Our Paper “Adaptive consensus-based distributed detection in WSN with unreliable links” accepted at IEEE ICASSP 2016
Event detection is a crucial tasks in wireless sensor networks. The importance of a fast response makes distributed strategies, where nodes exchange information just with their one hop neighbors to reach local decisions, more adequate than schemes where all nodes send observations to a central entity. Distributed detectors are usually based on average consensus, where all nodes iteratively communicate to asymptotically agree on a final result. In a realistic scenario, communications are subject to random failures, which impacts the performance of the consensus. We propose an alternative detector, which adapts to the statistical properties of the consensus and compensate deviations from the average. Simulation results show that this adaptive detector improves the performance and approximates to the one of the optimal detector.