Predictive congestion control based on collaborative information sharing for vehicular ad hoc networks.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorGomides, Thiago da Silva-
Autor(es): dc.creatorGrande, Robson Eduardo de-
Autor(es): dc.creatorMeneguette, Rodolfo Ipolito-
Autor(es): dc.creatorSouza, Fernanda Sumika Hojo de-
Autor(es): dc.creatorGuidoni, Daniel Ludovico-
Data de aceite: dc.date.accessioned2025-08-21T15:07:37Z-
Data de disponibilização: dc.date.available2025-08-21T15:07:37Z-
Data de envio: dc.date.issued2022-10-10-
Data de envio: dc.date.issued2022-10-10-
Data de envio: dc.date.issued2021-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/jspui/handle/123456789/15662-
Fonte completa do material: dc.identifierhttps://www.sciencedirect.com/science/article/pii/S1389128622001347#!-
Fonte completa do material: dc.identifierhttps://doi.org/10.1016/j.comnet.2022.108955-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1003008-
Descrição: dc.descriptionTraffic jams are an essential and continuous challenge in our cities, responsible for socioeconomic and environmental concerns and an ambitious traffic jams management agenda is urgent. The distributed solutions in the literature for Traffic Management Systems (TMS) are heavily based on beacon messages or proactive communication protocols to share vehicular traffic information among vehicles. Thus, these solutions are not scalable when the number of vehicles increases in the network — when there are traffic jams. To overcome these problems, we propose a new VANET-based traffic management system named CoNeCT: Predictive Congestion Control based on Collaborative Information Sharing for Vehicular Ad hoc Networks. CoNeCT’s primary goal is to support vehicles’ collaboration in analyzing, predicting, and managing congestion. The proposed system was designed to decrease the number of messages by using a novel road segment load assessment that improves traffic flow classification. Vehicles aware of traffic conditions share it with their neighbors, and they can also request traffic views whenever necessary. Additionally, vehicles can detect significant traffic variations and predict future traffic conditions to improve roads’ overall traffic conditions, mitigating the congestion before it arises. Results obtained from an extensive performance analysis show CoNeCT’s ability to reduce traffic congestion with a low impact on the wireless communication medium, outperforming the state-of-art systems.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectVehicular networks-
Palavras-chave: dc.subjectTraffic management system-
Palavras-chave: dc.subjectCommunication protocols-
Palavras-chave: dc.subjectV2V communication-
Palavras-chave: dc.subjectIntelligent transportation systems-
Título: dc.titlePredictive congestion control based on collaborative information sharing for vehicular ad hoc networks.-
Aparece nas coleções:Repositório Institucional - UFOP

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