Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm
dc.contributor.author | Lieira, Douglas D. [UNESP] | |
dc.contributor.author | Quessada, Matheus S. [UNESP] | |
dc.contributor.author | Cristiani, Andre L. | |
dc.contributor.author | De Grande, Robson E. | |
dc.contributor.author | Meneguette, Rodolfo I. | |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
dc.contributor.institution | Federal Institute of São Paulo (IFSP) | |
dc.contributor.institution | Universidade Federal de São Carlos (UFSCar) | |
dc.contributor.institution | Brock University (BrockU) | |
dc.contributor.institution | Universidade de São Paulo (USP) | |
dc.date.accessioned | 2023-07-29T12:30:00Z | |
dc.date.available | 2023-07-29T12:30:00Z | |
dc.date.issued | 2022-01-01 | |
dc.description.abstract | 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. | en |
dc.description.affiliation | Sao Paulo State University, SP | |
dc.description.affiliation | Federal Institute of São Paulo (IFSP), SP | |
dc.description.affiliation | Federal University of São Carlos (UFSCar), SP | |
dc.description.affiliation | Brock University (BrockU) | |
dc.description.affiliation | University of São Paulo (USP), SP | |
dc.description.affiliationUnesp | Sao Paulo State University, SP | |
dc.format.extent | 283-290 | |
dc.identifier | http://dx.doi.org/10.1109/DCOSS54816.2022.00054 | |
dc.identifier.citation | Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022, p. 283-290. | |
dc.identifier.doi | 10.1109/DCOSS54816.2022.00054 | |
dc.identifier.scopus | 2-s2.0-85139430474 | |
dc.identifier.uri | http://hdl.handle.net/11449/246035 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings - 18th Annual International Conference on Distributed Computing in Sensor Systems, DCOSS 2022 | |
dc.source | Scopus | |
dc.subject | bio-inspire algorithm | |
dc.subject | edge computing | |
dc.subject | particle swarm optimization | |
dc.subject | resource allocation | |
dc.title | Mechanism for Optimizing Resource Allocation in VANETs Based on the PSO Bio-inspired Algorithm | en |
dc.type | Trabalho apresentado em evento |