Distributed Change Detection via Average Consensus over Networks

Abstract

Distributed change-point detection has been a fundamental problem when performing real-time monitoring using sensor networks. We propose a distributed detection algorithm, where each sensor only exchanges CUSUM statistic with their neighbors based on the average consensus scheme, and an alarm is raised when local consensus statistic exceeds a prespecified global threshold. We provide theoretical performance bounds showing that the performance of the fully distributed scheme can match the centralized algorithms under some mild conditions. Numerical experiments demonstrate the good performance of the algorithm, especially, in detecting asynchronous changes.