Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/DCOSS54816.2022.00054 http://hdl.handle.net/11449/246035 |
Resumo: | With the increase of vehicles in cities and the technology used by these vehicles, there is also a need to use the technology made available by intelligent transport systems in an efficient and agile way. Edge computing services assist in the agile process of exchanging and sharing information and resources between vehicles. However, the limitations of edge services bring the need to optimize resource allocation processes. Thus, in this article we propose the MARIA, a mechanism for optimizing computational resources in Vehicular Ad Hoc Networks based on the particle swarm optimization bio-inspired algorithm. The ease of adaptation to various scenarios by a bio-inspired algorithm is presented in the work. In addition, the MARIA mechanism proved to be efficient when compared with techniques frequently used in the literature and was able to increase the amount of services accepted and reduced the amount of refused services. |
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Repositório Institucional da UNESP |
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Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithmbio-inspire algorithmedge computingparticle swarm optimizationresource allocationWith the increase of vehicles in cities and the technology used by these vehicles, there is also a need to use the technology made available by intelligent transport systems in an efficient and agile way. Edge computing services assist in the agile process of exchanging and sharing information and resources between vehicles. However, the limitations of edge services bring the need to optimize resource allocation processes. Thus, in this article we propose the MARIA, a mechanism for optimizing computational resources in Vehicular Ad Hoc Networks based on the particle swarm optimization bio-inspired algorithm. The ease of adaptation to various scenarios by a bio-inspired algorithm is presented in the work. In addition, the MARIA mechanism proved to be efficient when compared with techniques frequently used in the literature and was able to increase the amount of services accepted and reduced the amount of refused services.Sao Paulo State University, SPFederal Institute of São Paulo (IFSP), SPFederal University of São Carlos (UFSCar), SPBrock University (BrockU)University of São Paulo (USP), SPSao Paulo State University, SPUniversidade Estadual Paulista (UNESP)Federal Institute of São Paulo (IFSP)Universidade Federal de São Carlos (UFSCar)Brock University (BrockU)Universidade de São Paulo (USP)Lieira, Douglas D. [UNESP]Quessada, Matheus S. [UNESP]Cristiani, Andre L.De Grande, Robson E.Meneguette, Rodolfo I.2023-07-29T12:30:00Z2023-07-29T12:30:00Z2022-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject283-290http://dx.doi.org/10.1109/DCOSS54816.2022.00054Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022, p. 283-290.http://hdl.handle.net/11449/24603510.1109/DCOSS54816.2022.000542-s2.0-85139430474Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022info:eu-repo/semantics/openAccess2023-07-29T12:30:00Zoai:repositorio.unesp.br:11449/246035Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:55:11.570075Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
title |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
spellingShingle |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm Lieira, Douglas D. [UNESP] bio-inspire algorithm edge computing particle swarm optimization resource allocation |
title_short |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
title_full |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
title_fullStr |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
title_full_unstemmed |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
title_sort |
Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm |
author |
Lieira, Douglas D. [UNESP] |
author_facet |
Lieira, Douglas D. [UNESP] Quessada, Matheus S. [UNESP] Cristiani, Andre L. De Grande, Robson E. Meneguette, Rodolfo I. |
author_role |
author |
author2 |
Quessada, Matheus S. [UNESP] Cristiani, Andre L. De Grande, Robson E. Meneguette, Rodolfo I. |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) Federal Institute of São Paulo (IFSP) Universidade Federal de São Carlos (UFSCar) Brock University (BrockU) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Lieira, Douglas D. [UNESP] Quessada, Matheus S. [UNESP] Cristiani, Andre L. De Grande, Robson E. Meneguette, Rodolfo I. |
dc.subject.por.fl_str_mv |
bio-inspire algorithm edge computing particle swarm optimization resource allocation |
topic |
bio-inspire algorithm edge computing particle swarm optimization resource allocation |
description |
With the increase of vehicles in cities and the technology used by these vehicles, there is also a need to use the technology made available by intelligent transport systems in an efficient and agile way. Edge computing services assist in the agile process of exchanging and sharing information and resources between vehicles. However, the limitations of edge services bring the need to optimize resource allocation processes. Thus, in this article we propose the MARIA, a mechanism for optimizing computational resources in Vehicular Ad Hoc Networks based on the particle swarm optimization bio-inspired algorithm. The ease of adaptation to various scenarios by a bio-inspired algorithm is presented in the work. In addition, the MARIA mechanism proved to be efficient when compared with techniques frequently used in the literature and was able to increase the amount of services accepted and reduced the amount of refused services. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 2023-07-29T12:30:00Z 2023-07-29T12:30:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/DCOSS54816.2022.00054 Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022, p. 283-290. http://hdl.handle.net/11449/246035 10.1109/DCOSS54816.2022.00054 2-s2.0-85139430474 |
url |
http://dx.doi.org/10.1109/DCOSS54816.2022.00054 http://hdl.handle.net/11449/246035 |
identifier_str_mv |
Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022, p. 283-290. 10.1109/DCOSS54816.2022.00054 2-s2.0-85139430474 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
283-290 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128290355937280 |