Group'n Route: an edge learning-based clustering and efficient routing scheme leveraging social strength for the Internet of Vehicles

Magaia, Naercio, Ferreira, Pedro, Pereira, Paulo Rogério, Muhammad, Khan, Del Ser, Javi and Albuquerque, Victor Hugo C de (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. ISSN 1524-9050 (Accepted)

[img] PDF (© 2022 IEEE) - Accepted Version
Download (951kB)

Abstract

The 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.

Item Type: Article
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Keywords: Internet of Vehicles, edge learning, clustering, graph theory, routing, social strength
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Foundations of Software Systems
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 25 Apr 2022 08:07
Last Modified: 25 Apr 2022 08:15
URI: http://sro.sussex.ac.uk/id/eprint/105491

View download statistics for this item

📧 Request an update