Energy-Efficient UAV Trajectory Planning in Rechargeable IoT Networks

Abstract

Maintaining adequate energy in low-powered Internet of Things (IoT) nodes is crucial for developing several applications like smart homes, autonomous industries, etc. In this context, energy harvesting plays an essential role in improving the operational lifetime of the IoT nodes. Unmanned Aerial Vehicles (UAVs) have become a feasible option for reaching out to the low-powered IoT nodes in remote areas and recharging them by acting as efficient energy transmitter units. However, ensuring a sustainable and regular supply of power to these IoT nodes mainly depends on the trajectories of UAVs. In this context, the UAV trajectory optimization problem is first formulated. Subsequently, an energy-efficient UAV route planning algorithm (UAV-RPA) is proposed to generate the UAV trajectory to recharge the IoT nodes. The proposed algorithm minimizes the UAV-travel time by selecting an optimal sequence of IoT nodes such that the UAV trajectory length is minimized. Moreover, extensive simulations are also conducted under various network scenarios to evaluate the performance of the route planning algorithm. It is observed that the proposed UAV-RPA generates a minimal length UAV trajectory over an IoT network when compared to other UAV trajectory generation algorithms. Also, the average residual energy per IoT node in the network is also improved. This, in turn, improves the operational lifetime of self-sustaining UAV-powered IoT networks.