Title:	FORESAM—FOG paradigm-based resource allocation mechanism for vehicular clouds
Authors:	Pereira, Rickson Boukerche, Azzedine Silva, Marco A. C. da Nakamura, Luis H. V. Freitas, Heitor Rocha Filho, Geraldo P. Meneguette, Rodolfo I.
metadata.dc.identifier.orcid:	https://orcid.org/0000-0003-4883-5675 https://orcid.org/0000-0001-6080-7699 https://orcid.org/0000-0001-6795-2768 https://orcid.org/0000-0003-2982-4006
Assunto::	Sistema de transporte Alocação de recursos Modelos matemáticos Sistema inteligente
Issue Date:	2021
Publisher:	MDPI
Citation:	PEREIRA, Rickson et al. FORESAM—FOG paradigm-based resource allocation mechanism for vehicular clouds. Sensors, v. 21, n. 15, 5028, 2021. DOI: https://doi.org/10.3390/s21155028. Disponível em: https://www.mdpi.com/1424-8220/21/15/5028. Acesso em: 4 maio 2022.
Abstract:	The Intelligent Transport Systems (ITS) has the objective quality of transportation improvement through transportation system monitoring and management and makes the trip more comfortable and safer for drivers and passengers. The mobile clouds can assist the ITS in handling the resource management problem. However, resource allocation management in an ITS is challenging due to vehicular network characteristics, such as high mobility and dynamic topology. With that in mind, we propose the FORESAM, a mechanism for resources management and allocation based on a set of FOGs which control vehicular cloud resources in the urban environment. The mechanism is based on a more accurate mathematical model (Multiple Attribute Decision), which aims to assist the allocation decision of resources set that meets the period requested service. The simulation results have shown that the proposed solution allows a higher number of services, reducing the number of locks of services with its accuracy. Furthermore, its resource allocation is more balanced the provided a smaller amount of discarded services.
Licença::	(CC BY)
DOI:	https://doi.org/10.3390/s21155028
Appears in Collections:	Artigos publicados em periódicos e afins

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