AoI-Based Transmission Scheduling for Cyber-Physical Systems Over Fading Channel Against Eavesdropping

This paper investigates the transmission scheduling problem of cyber-physical systems (CPSs). Specifically, in a CPS, a sensor collects real-time data of the monitoring area and at each decision epoch, the system must determine whether to transmit data packets to the gateway through an unreliable wireless channel. Furthermore, we assume that the CPS is subject to an energy-harvesting (EH) eavesdropper, and the communication channel is wiretapped randomly when the harvested energy of the eavesdropper is sufficient. The objective is to obtain the optimal transmission scheduling to minimize the Age of Information (AoI) of the CPS while keeping the AoI of eavesdropper above a certain level. To achieve this, we first transform the system model into a Markov decision process (MDP). We then prove that the optimal transmission scheduling policy is a threshold behavior on the AoI of both the CPS and the eavesdropper, respectively. Based on the structural properties of the optimal policy, we have developed a new backward induction algorithm to compute the optimal AoI-based transmission scheduling and the performance index function with lower computational costs compared to the conventional induction algorithm. Finally, we verify the validity of the algorithm and the correctness of the theoretical results through simulations.