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The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle

With the low latency, high transmission rate, and high reliability provided by the fifth-generation mobile communication network (5G), many applications requiring ultra-low latency and high reliability (uRLLC) have become a hot research topic. Among these issues, the most important is the Internet o...

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Autores principales: Huang, Shih-Yun, Chen, Shih-Syun, Chen, Min-Xiou, Chang, Yao-Chung, Chao, Han-Chieh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840155/
https://www.ncbi.nlm.nih.gov/pubmed/35161884
http://dx.doi.org/10.3390/s22031140
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author Huang, Shih-Yun
Chen, Shih-Syun
Chen, Min-Xiou
Chang, Yao-Chung
Chao, Han-Chieh
author_facet Huang, Shih-Yun
Chen, Shih-Syun
Chen, Min-Xiou
Chang, Yao-Chung
Chao, Han-Chieh
author_sort Huang, Shih-Yun
collection PubMed
description With the low latency, high transmission rate, and high reliability provided by the fifth-generation mobile communication network (5G), many applications requiring ultra-low latency and high reliability (uRLLC) have become a hot research topic. Among these issues, the most important is the Internet of Vehicles (IoV). To maintain the safety of vehicle drivers and road conditions, the IoV can transmit through sensors or infrastructure to maintain communication quality and transmission. However, because 5G uses millimeter waves for transmission, a large number of base stations (BS) or lightweight infrastructure will be built in 5G, which will make the overall environment more complex than 4G. The lightweight infrastructure also has to be considered together. For these reasons, in 5G, there are two mechanisms for handover, horizontal, and vertical handover; hence, it must be discussed how to handle handover to obtain the best performance for the whole network. In this paper, to address handover selection, we consider delay time, energy efficiency, load balancing, and energy consumption and formulate it as a multi-objective optimization (MOO) problem. At the same time, we propose the handover of the mobile management mechanism based on location prediction combined with heuristic algorithms. The results show that our proposed mechanism is better than the distance-based one for energy efficiency, load, and latency. It optimizes by more than about 20% at most.
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spelling pubmed-88401552022-02-13 The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle Huang, Shih-Yun Chen, Shih-Syun Chen, Min-Xiou Chang, Yao-Chung Chao, Han-Chieh Sensors (Basel) Article With the low latency, high transmission rate, and high reliability provided by the fifth-generation mobile communication network (5G), many applications requiring ultra-low latency and high reliability (uRLLC) have become a hot research topic. Among these issues, the most important is the Internet of Vehicles (IoV). To maintain the safety of vehicle drivers and road conditions, the IoV can transmit through sensors or infrastructure to maintain communication quality and transmission. However, because 5G uses millimeter waves for transmission, a large number of base stations (BS) or lightweight infrastructure will be built in 5G, which will make the overall environment more complex than 4G. The lightweight infrastructure also has to be considered together. For these reasons, in 5G, there are two mechanisms for handover, horizontal, and vertical handover; hence, it must be discussed how to handle handover to obtain the best performance for the whole network. In this paper, to address handover selection, we consider delay time, energy efficiency, load balancing, and energy consumption and formulate it as a multi-objective optimization (MOO) problem. At the same time, we propose the handover of the mobile management mechanism based on location prediction combined with heuristic algorithms. The results show that our proposed mechanism is better than the distance-based one for energy efficiency, load, and latency. It optimizes by more than about 20% at most. MDPI 2022-02-02 /pmc/articles/PMC8840155/ /pubmed/35161884 http://dx.doi.org/10.3390/s22031140 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Huang, Shih-Yun
Chen, Shih-Syun
Chen, Min-Xiou
Chang, Yao-Chung
Chao, Han-Chieh
The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle
title The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle
title_full The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle
title_fullStr The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle
title_full_unstemmed The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle
title_short The Efficient Mobile Management Based on Metaheuristic Algorithm for Internet of Vehicle
title_sort efficient mobile management based on metaheuristic algorithm for internet of vehicle
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840155/
https://www.ncbi.nlm.nih.gov/pubmed/35161884
http://dx.doi.org/10.3390/s22031140
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