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Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey

The increasing demand for smart vehicles with many sensing capabilities will escalate data traffic in vehicular networks. Meanwhile, available network resources are limited. The emergence of AI implementation in vehicular network resource allocation opens the opportunity to improve resource utilizat...

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Detalles Bibliográficos
Autores principales: Nurcahyani, Ida, Lee, Jeong Woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512744/
https://www.ncbi.nlm.nih.gov/pubmed/34640858
http://dx.doi.org/10.3390/s21196542
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author Nurcahyani, Ida
Lee, Jeong Woo
author_facet Nurcahyani, Ida
Lee, Jeong Woo
author_sort Nurcahyani, Ida
collection PubMed
description The increasing demand for smart vehicles with many sensing capabilities will escalate data traffic in vehicular networks. Meanwhile, available network resources are limited. The emergence of AI implementation in vehicular network resource allocation opens the opportunity to improve resource utilization to provide more reliable services. Accordingly, many resource allocation schemes with various machine learning algorithms have been proposed to dynamically manage and allocate network resources. This survey paper presents how machine learning is leveraged in the vehicular network resource allocation strategy. We focus our study on determining its role in the mechanism. First, we provide an analysis of how authors designed their scenarios to orchestrate the resource allocation strategy. Secondly, we classify the mechanisms based on the parameters they chose when designing the algorithms. Finally, we analyze the challenges in designing a resource allocation strategy in vehicular networks using machine learning. Therefore, a thorough understanding of how machine learning algorithms are utilized to offer a dynamic resource allocation in vehicular networks is provided in this study.
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spelling pubmed-85127442021-10-14 Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey Nurcahyani, Ida Lee, Jeong Woo Sensors (Basel) Review The increasing demand for smart vehicles with many sensing capabilities will escalate data traffic in vehicular networks. Meanwhile, available network resources are limited. The emergence of AI implementation in vehicular network resource allocation opens the opportunity to improve resource utilization to provide more reliable services. Accordingly, many resource allocation schemes with various machine learning algorithms have been proposed to dynamically manage and allocate network resources. This survey paper presents how machine learning is leveraged in the vehicular network resource allocation strategy. We focus our study on determining its role in the mechanism. First, we provide an analysis of how authors designed their scenarios to orchestrate the resource allocation strategy. Secondly, we classify the mechanisms based on the parameters they chose when designing the algorithms. Finally, we analyze the challenges in designing a resource allocation strategy in vehicular networks using machine learning. Therefore, a thorough understanding of how machine learning algorithms are utilized to offer a dynamic resource allocation in vehicular networks is provided in this study. MDPI 2021-09-30 /pmc/articles/PMC8512744/ /pubmed/34640858 http://dx.doi.org/10.3390/s21196542 Text en © 2021 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 Review
Nurcahyani, Ida
Lee, Jeong Woo
Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey
title Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey
title_full Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey
title_fullStr Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey
title_full_unstemmed Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey
title_short Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey
title_sort role of machine learning in resource allocation strategy over vehicular networks: a survey
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512744/
https://www.ncbi.nlm.nih.gov/pubmed/34640858
http://dx.doi.org/10.3390/s21196542
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