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An Interest-Based Approach for Reducing Network Contentions in Vehicular Transportation Systems

Traffic management systems (TMS) are the key for dealing with mobility issues. Moreover, 5G and vehicular networking are expected to play an important role in supporting TMSs for providing a smarter, safer and faster transportation. In this way, several infrastructure-based TMSs have been proposed t...

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Detalles Bibliográficos
Autores principales: de Souza, Allan M., Maia, Guilherme, Braun, Torsten, Villas, Leandro A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6566315/
https://www.ncbi.nlm.nih.gov/pubmed/31137549
http://dx.doi.org/10.3390/s19102325
Descripción
Sumario:Traffic management systems (TMS) are the key for dealing with mobility issues. Moreover, 5G and vehicular networking are expected to play an important role in supporting TMSs for providing a smarter, safer and faster transportation. In this way, several infrastructure-based TMSs have been proposed to improve vehicular traffic mobility. However, in massively connected and multi-service smart city scenarios, infrastructure-based systems can experience low delivery ratios and high latency due to packet congestion in backhaul links on ultra-dense cells with high data traffic demand. In this sense, we propose I am not interested in it (IAN3I), an interest-based approach for reducing network contention and even avoid infrastructure dependence in TMS. IAN3I enables a fully-distributed traffic management and an opportunistic content sharing approach in which vehicles are responsible for storing and delivering traffic information only to vehicles interested in it. Simulation results under a realistic scenario have shown that, when compared to state-of-the-art approaches, IAN3I decreases the number of transmitted messages, packet collisions and latency in up to [Formula: see text] , [Formula: see text] and [Formula: see text] respectively while dealing with traffic efficiency properly, not affecting traffic management performance at all.