Data Collection in Wireless Sensor Networks: A Truck-Assisted Multi-UAV Method

Abstract

Unmanned aerial vehicles (UAVs) are endorsed as means to support efficient data collection from wireless sensor networks due to their flexibility and agility. However, the limited battery capacity of the UAVs becomes a bottleneck to the applications on many occasions, especially the networks deployed on the vast land. To this end, we consider a multi-UAV assisted data collection framework and propose a synchronized network to handle the energy issue, in which a truck carrying backup batteries moves together with the UAVs, acting as a "mobile charging station". Our goal is to minimize the total mission time for data collection from all the sensor nodes. We first develop a clustering algorithm to divide the region of interest into multiple clusters in a load-balanced way so as to minimize the number of movements of the UAVs, then formulate the trajectory optimization task as a coordinated multiple traveling salesman problem which is heuristically solved by a utilization-balancing trajectory planning algorithm. Numerical results indicate that our proposed scheme can effectively find the trajectories for the truck and UAVs. Moreover, our proposal sheds light on how to design a high-efficient and practical way for data gathering from large-scale wireless sensor networks.