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RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas

1
Laboratoire d’INtelligence Artificielle et des Technologies de l’Information, Department of Computer science, Faculty of New Technologies of Information and Communication, University of Kasdi Merbah, Ouargla BP 511 30000, Algeria
2
Laboratoire d’Informatique et de Mathématiques, University of Laghouat, Laghouat BP 37G 03000, Algeria
*
Author to whom correspondence should be addressed.
Electronics 2021, 10(2), 193; https://doi.org/10.3390/electronics10020193
Received: 15 December 2020 / Revised: 11 January 2021 / Accepted: 13 January 2021 / Published: 15 January 2021
(This article belongs to the Section Electrical and Autonomous Vehicles)
As a promising topic of research, Vehicular Cloud (VC) incorporates cloud computing and ad-hoc vehicular network (VANET). In VC, supplier vehicles provide their services to consumer vehicles in real-time. These services have a significant impact on the applications of internet access, storage and data. Due to the high-speed mobility of vehicles, users in consumer vehicles need a mechanism to discover services in their vicinity. Besides this, quality of service varies from one supplier vehicle to another; thus, consumer vehicles attempt to pick out the most appropriate services. In this paper, we propose a novel protocol named RSU-aided Cluster-based Vehicular Clouds protocol (RCVC), which constructs the VC using the Road Side Unit (RSU) directory and Cluster Head (CH) directory to make the resources of supplier vehicles more visible. While clusters of vehicles that move on the same road form a mobile cloud, the remaining vehicles form a different cloud on the road side unit. Furthermore, the consumption operation is achieved via the service selection method, which is managed by the CHs and RSUs based on a mathematical model to select the best services. Simulation results prove the effectiveness of our protocol in terms of service discovery and end-to-end delay, where we achieved service discovery and end-to-end delay of 3 × 10−3 s and 13 × 10−2 s, respectively. Moreover, we carried out an experimental comparison, revealing that the proposed method outperformed several states of the art protocols. View Full-Text
Keywords: vehicular cloud; VANET; cloud computing; vehicle clustering vehicular cloud; VANET; cloud computing; vehicle clustering
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MDPI and ACS Style

Ben bezziane, M.; Korichi, A.; Kerrache, C.A.; Fekair, M.e.A. RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas. Electronics 2021, 10, 193. https://doi.org/10.3390/electronics10020193

AMA Style

Ben bezziane M, Korichi A, Kerrache CA, Fekair MeA. RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas. Electronics. 2021; 10(2):193. https://doi.org/10.3390/electronics10020193

Chicago/Turabian Style

Ben bezziane, Mohamed, Ahmed Korichi, Chaker A. Kerrache, and Mohamed e.A. Fekair. 2021. "RCVC: RSU-Aided Cluster-Based Vehicular Clouds Architecture for Urban Areas" Electronics 10, no. 2: 193. https://doi.org/10.3390/electronics10020193

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