Resource-efficient and secure distributed state estimation over wireless sensor networks: a survey

Abstract

Wireless sensor networks (WSNs) are extensively adopted for remote monitoring and tracking scenarios, such as battlefield surveillance, target detection and tracking, traffic condition detection, power system monitoring and health monitoring, thanks to their promising benefits in terms of flexibility, reliability and cost-effectiveness. However, some critical WSN applications, such as intelligent transportation and smart grid monitoring, have stringent requirements in terms of resource budget and security. This paper provides a survey of the trending resource-efficient and secure techniques currently used with distributed estimation algorithms over WSNs. Recent progresses on these two major research trends are reviewed, respectively, for WSN-based monitoring systems. More specifically, the first part of the survey covers the state-of-the-art in resource-efficient distributed state estimation. The main results along this line of research are classified into protocol-based scheduling, static event-triggered scheduling, dynamic event-triggered scheduling and stochastic event-triggered scheduling. Then, in the second part, the latest results on secure distributed state estimation are reviewed, where secure distributed state estimation under data integrity attacks and data available attacks, and distributed attack detection are examined, respectively. Finally, several challenging issues in the context of distributed state estimation are discussed for potential future research.