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Trajectory optimization of laser-charged UAV to minimize the average age of information for wireless rechargeable sensor network.

Authors :
Luo, Chuanwen
Liu, Ning
Hou, Yunan
Hong, Yi
Chen, Zhibo
Li, Deying
Source :
Theoretical Computer Science. Feb2023, Vol. 945, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

This paper considers the laser-charged Unmanned Aerial Vehicle (UAV) assisted Wireless Rechargeable Sensor Network (WRSN), where rechargeable sensors are deployed in surveillance environment to monitor information, a UAV is not only used as aerial wireless mobile collector for gathering data from sensors but also used as mobile charger to replenish energy for sensors, Laser Beam Directors (LBDs) are uniformly deployed in the monitoring environment to charge UAV by emitting laser beams. In such network, we study the average Age of Information Optimization (AoIO) problem whose objective is to minimize the average AoI of data collected from sensors such that all data of the network are transported to the base station and the remaining energy of any sensor exceeds a certain threshold. We prove that the AoIO problem is NP-hard. To solve the AoIO problem, we first study the Total Flight Time Minimizing of UAV (TFTM) problem, which aims at finding an optimal charging solution of UAV to minimize the flight time of UAV based on the order of sensors visited by UAV. Then we prove that the TFTM problem is also NP-hard. Afterwards, we propose a heuristic algorithm to solve the TFTM problem by optimizing flight path, data collection, energy power transfer and laser charging of UAV. Based on the solution for the TFTM problem, we propose an approximation algorithm to solve the AoIO problem. Finally, we conduct extensive simulation experiments to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03043975
Volume :
945
Database :
Academic Search Index
Journal :
Theoretical Computer Science
Publication Type :
Academic Journal
Accession number :
161441275
Full Text :
https://doi.org/10.1016/j.tcs.2022.12.030