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ORIGINAL RESEARCH article

Front. Comms. Net.
Sec. IoT and Sensor Networks
Volume 5 - 2024 | doi: 10.3389/frcmn.2024.1390909

Efficient Multiple Unmanned Aerial Vehicles Assisted Data Collection Strategy in Power Infrastructure Construction Provisionally Accepted

 Chao Yang1* Qijie Lai2 Ronchang Xie2 Zhifei Yang2 Guibin Wu2 Zechao Hong2
  • 1Guangdong University of Technology, China
  • 2Guangdong Power Grid Corporation, China

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Efficient data collection and sharing perform the crucial part in the power infrastructure construction.However, in the outdoor remote area, the data collection efficiency is reduced for the sparse distribution of base stations (BS). Unmanned Aerial Vehicles (UAVs) can perform as the flying BS for the mobility and the line-of-sight transmission features. In this paper, we propose a multiple temporary UAV-assisted data collection system in power infrastructure scenario, multiple temporary UAVs are employed to perform as relay or edge computing node. To improve the system performance, the task processing model selection, the communication resource allocation, the UAV selection and task migration are jointly optimized. We design a QMIX-based multi-agent deep reinforcement learning algorithm to find the final optimal solutions. Simulation results shows that the proposed algorithm has better convergence and lower system costs, compared with the current existing algorithms.

Keywords: Data Collection, UAV, Task migration, Multi-agent DRL, QMix

Received: 24 Feb 2024; Accepted: 13 May 2024.

Copyright: © 2024 Yang, Lai, Xie, Yang, Wu and Hong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Chao Yang, Guangdong University of Technology, Guangzhou, China