Energy-Constrained UAV Flight Scheduling for IoT Data Collection With 60 GHz Communication

• Published in: IEEE transactions on vehicular technology Vol. 71; no. 10; pp. 10991 - 11005
• Main Authors: Wu, Wenjia, Sun, Shengyu, Shan, Feng, Yang, Ming, Luo, Junzhou
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 60 GHz communica- tion; Algorithms; Approximation; Approximation algorithms; Autonomous aerial vehicles; Bandwidths; Cameras; Communication; Data collection; Data storage; Electronic devices; energy constraint; Energy consumption; Energy storage; flight scheduling; Ground stations; High definition; Internet of Things; Line of sight communication; Mathematical analysis; Scheduling; Sensors; UAV-aided data collection; Unmanned aerial vehicles
• DOI: 10.1109/TVT.2022.3184869
• ISSN: 0018-9545

In recent years, the data from Internet of Things (IoT) devices is growing at a rapid pace, and the data collection issues have attracted more and more attention. Distinct from existing solutions which usually adopted traditional wireless technologies achieving low-bandwidth data connections towards IoT devices, this paper adopts the 60 GHz communication technology which is with increasing maturity, providing high-bandwidth wireless transmission for data-intensive IoT devices, such as high-definition (HD) cameras. However, 60 GHz links are subject to line-of-sight short communication range, therefore, we propose to use unmanned aerial vehicles (UAVs) to fly over data-intensive IoT devices and achieve short-range high-throughput 60 GHz transmission in this paper. Moreover, for a set of HD cameras deployed in the linear scenario, multiple UAV flights are assigned to collect data by 60 GHz communication. To this end, we investigate the UAV flight scheduling (UFS) problem which aims to minimize the number of UAV flights while satisfying the data requirements of all ground cameras (GCs) with limitations of UAV's energy and data storage. We prove that the UFS problem is NP-hard and design efficient algorithms with constant theoretical approximation ratios. Specifically, we first study a special case of the UFS problem where all the cameras are on the same direction of the UAV ground station, and propose two algorithms NF_SUFS and FF_SUFS, whose approximation ratios are both proved to be 2 by theoretical analysis. Then, we extend the algorithms to a more general case with the cameras on both directions of the ground station along the road, and put forward the FF_UFS algorithm that achieves an approximation ratio of 3. Finally, we conduct experiments to validate the effectiveness and efficiency of our algorithms.