Optimal Decentralized Sensor Scheduling for State Estimation Over Heterogeneous Multi-Hop Networks in Cyber-Physical Systems

In this letter, an energy-efficient estimation-oriented sensor scheduling problem over heterogeneous multi-hop sensor networks in cyber-physical systems (CPSs) is studied. Different from most existing literature, we mainly consider the scenario where only local information can be accessed for decision making for each hop, and additionally, different hops may share different power constraints and communication parameters. Based on this, a totally decentralized scheduling scheme has been provided, where a stochastically triggered form is proposed with a Markovian model adopted to formulate the state transition relationship between the adjacent hops. For the propose of calculation of the switching threshold and selection probabilities, an explicit expression for parameters determination is further properly designed to overcome the coupling property between hops. It can be proved that the global optimality can be achieved under our proposed decentralized scheduling scheme, and additionally, capturing conspicuous increase in performance with respect to other baseline schemes. Numerical simulation and comparisons with the random schedule, optimal offline schedule and state-of-the-art method have demonstrated the correctness and effectiveness of our proposed scheduling scheme and theoretical results.