Request–Response and Censoring-Based Energy-Efficient Decentralized Change-Point Detection With IoT Applications

Change-point detection (CPD) from streaming data is a fundamental problem in statistical signal processing and has wide applications in wireless sensor networks and the Internet of Things (IoT), such as environmental monitoring and physical activity detection. In various detection schemes, decentralized detection without fusion center is becoming increasingly popular for IoT applications since it enjoys the benefit of strong robustness and security. However, it faces the big challenge of high energy consumption. In this work, we propose an energy-efficient decentralized CPD algorithm called request-response and censoring-based cumulative sum. Specifically, we design a novel communication strategy based on request-response and censoring scheme, which could help the sensors extract useful information from the neighbor sets with a low amount of communication. Furthermore, to provide a guideline on selecting the parameters involved in our algorithm, we theoretically analyze the performance of the proposed algorithm under a simplification for the most interesting cases, in terms of two standard criteria average running length (ARL) and expected detection delay (EDD). Numerical simulations are conducted to verify the effectiveness of the proposed algorithm. Moreover, we test the feasibility of the proposed algorithm in the physical activity CPD task. The experimental results on the real-world data set demonstrate its high energy efficiency and small detection delay.