A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds

Detalhes bibliográficos
Autor(a) principal: Quessada, Matheus S. [UNESP]
Data de Publicação: 2021
Outros Autores: Lieira, Douglas D. [UNESP], Pereira, Rickson S. [UNESP], De Grande, Robson E. [UNESP], Meneguette, Rodolfo I. [UNESP]
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1109/DCOSS52077.2021.00042
http://hdl.handle.net/11449/223312
Resumo: The growth of vehicles in cities brings significant socioeconomic problems and new challenges. With that growth, the amount of information generated by vehicles and their devices also increments and can improve the network using Vehicular Ad Hoc Networks (VANET). VANETs make the communication between vehicles and infrastructures possible to exchange information and share resources. To assist VANETs, another concept called Vehicular Cloud Computing (VCC) brings the Cloud paradigms to this scenario. In this paper, we propose a Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds, called NAUTILUS. The algorithm uses the metaheuristic to optimize the search process for defining pseudo-optimal decision-making of the allocation process in a Vehicular Cloud. We also consider a fog-based paradigm to assist the proposed mechanism in the allocation process. We allocate the following resources from the vehicles: storage, memory, runtime, and processing. The NAUTILUS was compared to two other algorithms that use traditional search techniques: a Greedy approach and an Analytic Hierarchy Process (AHP) approach. In the comparison process, we evaluate the number of blocked, attended, and denied services. Simulations results show that the NAUTILUS presented better efficiency than Greedy and AHP approaches in all three performance aspects: blocking fewer, attending more, and denying fewer services.
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spelling A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Cloudsfogmetaheuristicresource allocationVehicular Ad Hoc NetworksVehicular CloudThe growth of vehicles in cities brings significant socioeconomic problems and new challenges. With that growth, the amount of information generated by vehicles and their devices also increments and can improve the network using Vehicular Ad Hoc Networks (VANET). VANETs make the communication between vehicles and infrastructures possible to exchange information and share resources. To assist VANETs, another concept called Vehicular Cloud Computing (VCC) brings the Cloud paradigms to this scenario. In this paper, we propose a Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds, called NAUTILUS. The algorithm uses the metaheuristic to optimize the search process for defining pseudo-optimal decision-making of the allocation process in a Vehicular Cloud. We also consider a fog-based paradigm to assist the proposed mechanism in the allocation process. We allocate the following resources from the vehicles: storage, memory, runtime, and processing. The NAUTILUS was compared to two other algorithms that use traditional search techniques: a Greedy approach and an Analytic Hierarchy Process (AHP) approach. In the comparison process, we evaluate the number of blocked, attended, and denied services. Simulations results show that the NAUTILUS presented better efficiency than Greedy and AHP approaches in all three performance aspects: blocking fewer, attending more, and denying fewer services.Sao Paulo State University SPSao Paulo State University SPUniversidade Estadual Paulista (UNESP)Quessada, Matheus S. [UNESP]Lieira, Douglas D. [UNESP]Pereira, Rickson S. [UNESP]De Grande, Robson E. [UNESP]Meneguette, Rodolfo I. [UNESP]2022-04-28T19:49:58Z2022-04-28T19:49:58Z2021-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject197-204http://dx.doi.org/10.1109/DCOSS52077.2021.00042Proceedings - 17th Annual International Conference on Distributed Computing in Sensor Systems, DCOS 2021, p. 197-204.http://hdl.handle.net/11449/22331210.1109/DCOSS52077.2021.000422-s2.0-85123311795Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings - 17th Annual International Conference on Distributed Computing in Sensor Systems, DCOS 2021info:eu-repo/semantics/openAccess2022-04-28T19:49:58Zoai:repositorio.unesp.br:11449/223312Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T15:29:38.809760Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
title A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
spellingShingle A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
Quessada, Matheus S. [UNESP]
fog
metaheuristic
resource allocation
Vehicular Ad Hoc Networks
Vehicular Cloud
title_short A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
title_full A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
title_fullStr A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
title_full_unstemmed A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
title_sort A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
author Quessada, Matheus S. [UNESP]
author_facet Quessada, Matheus S. [UNESP]
Lieira, Douglas D. [UNESP]
Pereira, Rickson S. [UNESP]
De Grande, Robson E. [UNESP]
Meneguette, Rodolfo I. [UNESP]
author_role author
author2 Lieira, Douglas D. [UNESP]
Pereira, Rickson S. [UNESP]
De Grande, Robson E. [UNESP]
Meneguette, Rodolfo I. [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Quessada, Matheus S. [UNESP]
Lieira, Douglas D. [UNESP]
Pereira, Rickson S. [UNESP]
De Grande, Robson E. [UNESP]
Meneguette, Rodolfo I. [UNESP]
dc.subject.por.fl_str_mv fog
metaheuristic
resource allocation
Vehicular Ad Hoc Networks
Vehicular Cloud
topic fog
metaheuristic
resource allocation
Vehicular Ad Hoc Networks
Vehicular Cloud
description The growth of vehicles in cities brings significant socioeconomic problems and new challenges. With that growth, the amount of information generated by vehicles and their devices also increments and can improve the network using Vehicular Ad Hoc Networks (VANET). VANETs make the communication between vehicles and infrastructures possible to exchange information and share resources. To assist VANETs, another concept called Vehicular Cloud Computing (VCC) brings the Cloud paradigms to this scenario. In this paper, we propose a Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds, called NAUTILUS. The algorithm uses the metaheuristic to optimize the search process for defining pseudo-optimal decision-making of the allocation process in a Vehicular Cloud. We also consider a fog-based paradigm to assist the proposed mechanism in the allocation process. We allocate the following resources from the vehicles: storage, memory, runtime, and processing. The NAUTILUS was compared to two other algorithms that use traditional search techniques: a Greedy approach and an Analytic Hierarchy Process (AHP) approach. In the comparison process, we evaluate the number of blocked, attended, and denied services. Simulations results show that the NAUTILUS presented better efficiency than Greedy and AHP approaches in all three performance aspects: blocking fewer, attending more, and denying fewer services.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-01
2022-04-28T19:49:58Z
2022-04-28T19:49:58Z
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/DCOSS52077.2021.00042
Proceedings - 17th Annual International Conference on Distributed Computing in Sensor Systems, DCOS 2021, p. 197-204.
http://hdl.handle.net/11449/223312
10.1109/DCOSS52077.2021.00042
2-s2.0-85123311795
url http://dx.doi.org/10.1109/DCOSS52077.2021.00042
http://hdl.handle.net/11449/223312
identifier_str_mv Proceedings - 17th Annual International Conference on Distributed Computing in Sensor Systems, DCOS 2021, p. 197-204.
10.1109/DCOSS52077.2021.00042
2-s2.0-85123311795
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings - 17th Annual International Conference on Distributed Computing in Sensor Systems, DCOS 2021
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 197-204
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
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