Data collection of wireless sensor network based on trajectory optimization of laser-charged UAV

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS High-Confidence Computing Pub Date : 2023-11-24 DOI:10.1016/j.hcc.2023.100181
Chuanwen Luo , Jian Zhang , Jin Qian , Yi Hong , Zhibo Chen , Yunan Hou , Xiujuan Zhang , Yuqing Zhu
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Abstract

Unmanned Aerial Vehicle (UAV) can be used as wireless aerial mobile base station for collecting data from sensors in UAV-based Wireless Sensor Networks (WSNs), which is crucial for providing seamless services and improving the performance in the next generation wireless networks. However, since the UAV are powered by batteries with limited energy capacity, the UAV cannot complete data collection tasks of all sensors without energy replenishment when a large number of sensors are deployed over large monitoring areas. To overcome this problem, we study the Real-time Data Collection with Laser-charging UAV (RDCL) problem, where the UAV is utilized to collect data from a specified WSN and is recharged using Laser Beam Directors (LBDs). This problem aims to collect all sensory data from the WSN and transport it to the base station by optimizing the flight trajectory of UAV such that real-time data performance is ensured It has been proven that the RDCL problem is NP-hard. To address this, we initially focus on studying two sub-problems, the Trajectory Optimization of UAV for Data Collection (TODC) problem and the Charging Trajectory Optimization of UAV (CTO) problem, whose objectives are to find the optimal flight plans of UAV in the data collection areas and charging areas, respectively. Then we propose an approximation algorithm to solve each of them with the constant factor. Subsequently, we present an approximation algorithm that utilizes the solutions obtained from TODC and CTO problems to address the RDCL problem. Finally, the proposed algorithm is verified by extensive simulations.

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基于激光充电无人机轨迹优化的无线传感器网络数据采集
无人飞行器(UAV)可用作无线空中移动基站,用于收集基于无人飞行器的无线传感器网络(WSN)中传感器的数据,这对于提供无缝服务和提高下一代无线网络的性能至关重要。然而,由于无人机由能量有限的电池供电,当大量传感器部署在大面积监测区域时,无人机在没有能量补充的情况下无法完成所有传感器的数据收集任务。为了克服这一问题,我们研究了激光充电无人机实时数据收集(RDCL)问题,即利用无人机从指定的 WSN 收集数据,并使用激光束导引器(LBD)为无人机充电。该问题旨在通过优化无人机的飞行轨迹,从 WSN 收集所有感知数据并传输到基站,从而确保数据的实时性。为此,我们首先重点研究了两个子问题,即无人机数据采集轨迹优化(TODC)问题和无人机充电轨迹优化(CTO)问题,其目标分别是找到无人机在数据采集区域和充电区域的最优飞行计划。然后,我们提出了一种近似算法来求解这两个问题。随后,我们提出了一种近似算法,利用从 TODC 和 CTO 问题中获得的解来解决 RDCL 问题。最后,我们通过大量仿真验证了所提出的算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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