Energy-Efficient UAV Routing for Wireless Sensor Networks

• Published in: IEEE transactions on vehicular technology Vol. 69; no. 2; pp. 1741 - 1750
• Main Authors: Baek, Jaeuk, Han, Sang Ik, Han, Youngnam
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.02.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computational geometry; Computer simulation; Convexity; Data collection; Data communication; Data transmission; Energy; Energy consumption; Energy-efficient data collection; Erbium; Hovering; Internet of Things; Optimization; Residual energy; Robot sensing systems; Route selection; Sensors; UAV flight route; Unmanned aerial vehicles; Voronoi diagram; Voronoi graphs; Wireless networks; Wireless sensor network; Wireless sensor networks
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2019.2959808

Recently, an unmanned aerial vehicle (UAV) has been widely adopted to make efficient use of network resources in such areas as internet of things (IoT), sensor networks and three dimensional (3D) wireless networks. Especially, in wireless sensor networks (WSNs) where energy consumption of sensors in data transmission is the most conspicuous feature, data collection by UAV provides a promising solution. To address this issue, we consider a UAV-enabled WSN, where a UAV is dispatched to collect data from sensors distributed in networks. We formulate an optimization problem to maximize the minimum residual energy of sensors after data transmission for energy-efficient UAV routing subject to data collection and UAV traveling distance constraints. To solve the non-convex optimization problem, we first derive a feasible solution, i.e., the shortest UAV route that guarantees data collection at all the sensors, where a Voronoi diagram is modified to find a set of UAV hovering locations. The proposed algorithm preferentially determines each UAV hovering location at Voronoi vertex so that UAV can collect data from as many adjacent sensors as possible. Then with an initial shortest UAV route, a UAV route is proposed by adjusting each UAV hovering location sequentially based on sensor energy status, which is easily accomplished by the properties of Voronoi diagram. Lastly, to find the proposed solution more quickly, we propose a sensor-energy based initial UAV route determination method. Simulation results are provided to validate the performance of our proposed algorithm, and to compare with other UAV route determination schemes.