A Bat Bio-inspired Mechanism for Resource Allocation in Vehicular Clouds
Autor(a) principal: | |
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Data de Publicação: | 2021 |
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/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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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 |
|
_version_ |
1808128520152416256 |