Group'n Route: An Edge Learning-Based Clustering and Efficient Routing Scheme Leveraging Social Strength for the Internet of Vehicles

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dc.contributor.authorMagaia, Naercio
dc.contributor.authorFerreira, Pedro
dc.contributor.authorPereira, Paulo Rogerio
dc.contributor.authorMuhammad, Khan
dc.contributor.authorSer, Javier Del
dc.contributor.authorDe Albuquerque, Victor Hugo C.
dc.contributor.institutionIA
dc.date.issued2022-10-01
dc.descriptionPublisher Copyright: © 2000-2011 IEEE.
dc.description.abstractThe Internet of Vehicles (IoV) is undoubtedly at the core of the future of intelligent transportation. It will prevail over the road ecosystem, and it will have a huge impact on our lives throughout the provision of seamless connectivity among diverse transportation means. For the network to operate efficiently, the data needs to be quickly spread throughout the network, which requires low computational and bandwidth overheads. However, the dynamics of vehicular environments due to frequent node mobility poses many challenges to realize efficient data dissemination. This work addresses this type of problem by proposing a novel clustering algorithm at the edge of the network and an efficient message routing approach, which is known as Group'n Route (GnR). Both mechanisms resort to machine learning and graph metrics that reflect the social relationships between the nodes. Our performance evaluation reveals that the clustering algorithm yields stable results with varying road scenarios, which are becoming an advisable approach in the presence of mobile IoV nodes. Also, the designed routing protocol achieves two orders of magnitude smaller overhead and almost double the delivery rate when it is compared to traditional routing protocols, which thereby justify that the combination of our two proposed clustering and routing methods are a plausible alternative to support IoV communications in real-world setups.en
dc.description.statusPeer reviewed
dc.format.extent13
dc.identifier.citationMagaia , N , Ferreira , P , Pereira , P R , Muhammad , K , Ser , J D & De Albuquerque , V H C 2022 , ' Group'n Route : An Edge Learning-Based Clustering and Efficient Routing Scheme Leveraging Social Strength for the Internet of Vehicles ' , IEEE Transactions on Intelligent Transportation Systems , vol. 23 , no. 10 , pp. 19589-19601 . https://doi.org/10.1109/TITS.2022.3171978
dc.identifier.doi10.1109/TITS.2022.3171978
dc.identifier.issn1524-9050
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85130469745&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofIEEE Transactions on Intelligent Transportation Systems
dc.relation.projectIDHorizon 2020 Framework Programme, H2020, 101006411
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subject.keywordsclustering
dc.subject.keywordsedge learning
dc.subject.keywordsgraph theory
dc.subject.keywordsInternet of Vehicles
dc.subject.keywordsrouting
dc.subject.keywordssocial strength
dc.subject.keywordsAutomotive Engineering
dc.subject.keywordsMechanical Engineering
dc.subject.keywordsComputer Science Applications
dc.subject.keywordsSDG 11 - Sustainable Cities and Communities
dc.titleGroup'n Route: An Edge Learning-Based Clustering and Efficient Routing Scheme Leveraging Social Strength for the Internet of Vehiclesen
dc.typejournal article
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