Simultaneous Sensor Placement and Scheduling for Fusion-Based Detection in RF-Powered Sensor Networks

When deploying RF-powered sensor networks for mission-critical applications such as security surveillance, it is often required to maximize or guarantee the quality of surveillance. Both placing and scheduling the charging/work modes of sensors are of key importance in order to ensure a satisfying quality of surveillance continuously. Traditionally, sensor placement and scheduling have been considered separately; one first decides where to place the sensors, and then when to activate them. In this paper, we study simultaneous sensor placement and charging/working scheduling problem for fusion-based detection in RF-powered sensor networks. We formulate the problem as a constrained optimization problem and prove its NP-completeness. Two greedy heuristic algorithms, JOGA-FFR and JOGA-DFR based on fixed and dynamic fusion radiuses respectively, are presented to solve the problem. We validate our approaches through extensive numerical simulations as well as simulations based on real data traces collected from a vehicle detection experiment. The results show that, our proposed algorithms always outperform TSGA, an algorithm that optimizes sensor placement and scheduling separately, in all the simulation scenarios, and are near optimal in small-scale networks. Besides, JOGA-DFR slightly outperforms JOGA-FFR under certain specific sensing model settings, but has higher time complexity than JOGA-FFR.