Efficient Non-preemptive On-demand Charging Scheduling Scheme for Wireless Rechargeable Sensor Networks

Recently, energy provisioning problem has become one of the leading research interests in Wireless Sensor Networks (WSNs). Deploying Mobile Charger Vehicles (MCVs) (e.g., robots, drones) equipped with high capacity-battery and Wireless Power Transfer (WPT) transmitter to charge the sensor nodes in the network wirelessly, is a promising solution. Existing scheduling policies mostly concentrated on charging tasks scheduling, but neglected the influences of network topology and energy threshold distribution. Furthermore, schedulability test of existing studies remain infeasible and we can’t guarantee implementing them for larger set of tasks, making them unsuitable for real-time WRSNs. To fill this gap, in this paper, first, we propose hexagonal clustered-based deployment of sensor nodes and MCVs to provide large coverage and a robust connected network through alternative routes. Second, we propose an efficient Non-Preemptive Priority on-Demand Charging scheduling (NPDC) scheme for the mobile chargers to schedule the charging tasks according to Earliest Deadline First EDF algorithm. Third, we propose an energy threshold distribution and algorithm to assign threshold value for nodes and optimize the arrivals of charge requests. Fourth, we propose a traffic intensity-based partial charging distribution to minimize the dead node density. Finally, extensive simulations have been conducted to evaluate the proposed algorithms. The results demonstrate that our proposed algorithms achieve good performance in terms of queue length, dead nodes density, response time, and energy efficiency.