An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment

As the computing capacity of existing mobile devices cannot fully meet the needs of users for communication quality, a computing resource allocation strategy for 5G communication in the Internet of Things (IoT) environment is proposed by applying UAV-assisted edge computing. First, a system model is...

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Main Author: Hao Liu
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Robotics
Online Access:http://dx.doi.org/10.1155/2022/9397783
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author Hao Liu
author_facet Hao Liu
author_sort Hao Liu
collection DOAJ
description As the computing capacity of existing mobile devices cannot fully meet the needs of users for communication quality, a computing resource allocation strategy for 5G communication in the Internet of Things (IoT) environment is proposed by applying UAV-assisted edge computing. First, a system model is constructed with the UAV deployed with mobile edge computing (MEC) servers to provide assisted computing services for multiple users on the ground. Based on the optimization of the UAV trajectory, communication scheduling, and the energy consumption model of the UAV, the problem of the total computational cost minimization is formulated. Then, the genetic algorithm is improved by introducing a penalty function to solve this problem, in which selection, crossover, and mutation operations are iterated to obtain the optimal allocation strategy for computational resources. Finally, a simulation platform is constructed to analyze the proposed method. The results show that the total cost and total time of the proposed strategy are better than other comparison strategies.
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issn 1687-9619
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publishDate 2022-01-01
publisher Wiley
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series Journal of Robotics
spelling doaj-art-f07e9937d845486faa82c96b5061d7b62025-02-03T01:23:14ZengWileyJournal of Robotics1687-96192022-01-01202210.1155/2022/9397783An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT EnvironmentHao Liu0Zhengzhou Health Vocational CollegeAs the computing capacity of existing mobile devices cannot fully meet the needs of users for communication quality, a computing resource allocation strategy for 5G communication in the Internet of Things (IoT) environment is proposed by applying UAV-assisted edge computing. First, a system model is constructed with the UAV deployed with mobile edge computing (MEC) servers to provide assisted computing services for multiple users on the ground. Based on the optimization of the UAV trajectory, communication scheduling, and the energy consumption model of the UAV, the problem of the total computational cost minimization is formulated. Then, the genetic algorithm is improved by introducing a penalty function to solve this problem, in which selection, crossover, and mutation operations are iterated to obtain the optimal allocation strategy for computational resources. Finally, a simulation platform is constructed to analyze the proposed method. The results show that the total cost and total time of the proposed strategy are better than other comparison strategies.http://dx.doi.org/10.1155/2022/9397783
spellingShingle Hao Liu
An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
Journal of Robotics
title An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
title_full An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
title_fullStr An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
title_full_unstemmed An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
title_short An UAV-Assisted Edge Computing Resource Allocation Strategy for 5G Communication in IoT Environment
title_sort uav assisted edge computing resource allocation strategy for 5g communication in iot environment
url http://dx.doi.org/10.1155/2022/9397783
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