Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment

In a vehicular ad hoc network (VANET), roadside units (RSUs) are installed at roadside and intersections to process vehicle-to-infrastructure communication, collect and analyse intelligent vehicle traffic data, send information to vehicles, and achieve early warning of safe driving of vehicles. Owni...

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Autores principales:	Feng Wang, Chenle Wang, Kan Wang, Qiaoyong Jiang, Bin Wang, Wenjuan He
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology T Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/6c082ef3409845b9b40a49300f17325f
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spelling	oai:doaj.org-article:6c082ef3409845b9b40a49300f17325f2021-11-22T01:11:22ZMultiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment1530-867710.1155/2021/4207130https://doaj.org/article/6c082ef3409845b9b40a49300f17325f2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/4207130https://doaj.org/toc/1530-8677In a vehicular ad hoc network (VANET), roadside units (RSUs) are installed at roadside and intersections to process vehicle-to-infrastructure communication, collect and analyse intelligent vehicle traffic data, send information to vehicles, and achieve early warning of safe driving of vehicles. Owning to the high cost of implementing and maintaining RSUs, it is of vital importance to determine where and how many RSUs to deploy. Optimal RSU deployment requires both a small number of RSUs and the maximum coverage of vehicle running process, which constitutes a conflicting multiobjective problem. Nevertheless, existing works do not explicitly utilize multiobjective algorithm to solve the RSU deployment problem. Therefore, a multiobjective differential evolution approach is proposed in this work to solve the problem. Firstly, to conquer the complexity of urban road RSU deployment, the static model is established. Secondly, in the proposed multiobjective differential evolution with discrete elitist guide (MODE-deg), the sigmoid function is applied to discrete individual values. Finally, elitist individuals are selected based on crowding distance ranking and nondominated ranking to generate new individuals, which further improve the convergence speed and population performance. Experimental results show that MODE-deg can generate the optimal nondominant solution set with good convergence and diversity, in contrast to other multiobjective evolutionary algorithms in five test functions of ZDT.Feng WangChenle WangKan WangQiaoyong JiangBin WangWenjuan HeHindawi-WileyarticleTechnologyTTelecommunicationTK5101-6720ENWireless Communications and Mobile Computing, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Telecommunication TK5101-6720
spellingShingle	Technology T Telecommunication TK5101-6720 Feng Wang Chenle Wang Kan Wang Qiaoyong Jiang Bin Wang Wenjuan He Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment
description	In a vehicular ad hoc network (VANET), roadside units (RSUs) are installed at roadside and intersections to process vehicle-to-infrastructure communication, collect and analyse intelligent vehicle traffic data, send information to vehicles, and achieve early warning of safe driving of vehicles. Owning to the high cost of implementing and maintaining RSUs, it is of vital importance to determine where and how many RSUs to deploy. Optimal RSU deployment requires both a small number of RSUs and the maximum coverage of vehicle running process, which constitutes a conflicting multiobjective problem. Nevertheless, existing works do not explicitly utilize multiobjective algorithm to solve the RSU deployment problem. Therefore, a multiobjective differential evolution approach is proposed in this work to solve the problem. Firstly, to conquer the complexity of urban road RSU deployment, the static model is established. Secondly, in the proposed multiobjective differential evolution with discrete elitist guide (MODE-deg), the sigmoid function is applied to discrete individual values. Finally, elitist individuals are selected based on crowding distance ranking and nondominated ranking to generate new individuals, which further improve the convergence speed and population performance. Experimental results show that MODE-deg can generate the optimal nondominant solution set with good convergence and diversity, in contrast to other multiobjective evolutionary algorithms in five test functions of ZDT.
format	article
author	Feng Wang Chenle Wang Kan Wang Qiaoyong Jiang Bin Wang Wenjuan He
author_facet	Feng Wang Chenle Wang Kan Wang Qiaoyong Jiang Bin Wang Wenjuan He
author_sort	Feng Wang
title	Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment
title_short	Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment
title_full	Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment
title_fullStr	Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment
title_full_unstemmed	Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment
title_sort	multiobjective differential evolution with discrete elite guide in internet of vehicles roadside unit deployment
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/6c082ef3409845b9b40a49300f17325f
work_keys_str_mv	AT fengwang multiobjectivedifferentialevolutionwithdiscreteeliteguideininternetofvehiclesroadsideunitdeployment AT chenlewang multiobjectivedifferentialevolutionwithdiscreteeliteguideininternetofvehiclesroadsideunitdeployment AT kanwang multiobjectivedifferentialevolutionwithdiscreteeliteguideininternetofvehiclesroadsideunitdeployment AT qiaoyongjiang multiobjectivedifferentialevolutionwithdiscreteeliteguideininternetofvehiclesroadsideunitdeployment AT binwang multiobjectivedifferentialevolutionwithdiscreteeliteguideininternetofvehiclesroadsideunitdeployment AT wenjuanhe multiobjectivedifferentialevolutionwithdiscreteeliteguideininternetofvehiclesroadsideunitdeployment
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Multiobjective Differential Evolution with Discrete Elite Guide in Internet of Vehicles Roadside Unit Deployment

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