Abstract
Nowadays, Internet of Vehicles (IoV) are considered as the most important promoter domain in the Intelligent Transportation System (ITS). Vehicles in IoV are characterized by a high nodes’ mobility, high nodes’ number and high data storage. However, IoV suffer from many challenges in order to achieve robust communication between vehicles such as frequent link disconnection, delay, and network overhead. In the traditional Vehicular Ad hoc NETworks (VANETs), these problems have often been solved by using clustering algorithms. Clustering in IoV can overcome and minimize the communication problems that face vehicles by reducing the network overhead and ensure some Quality of Service (QoS) to make network connectivity more stable. In this work, we propose a new Geo-graphical Information based Clustering Algorithm “GICA” destined to IoV environment. The proposal aims to maintain the cluster structure while respecting the quality of service requirements as the network evolves. We evaluated our proposed approach using the NS3 simulator and the realistic mobility model SUMO.
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Gasmi, R., Aliouat, M., Seba, H. (2021). Geographical Information Based Clustering Algorithm for Internet of Vehicles. In: Renault, É., Boumerdassi, S., Mühlethaler, P. (eds) Machine Learning for Networking. MLN 2020. Lecture Notes in Computer Science(), vol 12629. Springer, Cham. https://doi.org/10.1007/978-3-030-70866-5_7
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DOI: https://doi.org/10.1007/978-3-030-70866-5_7
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