Abstract
Road Side Units (RSUs) have a crucial role in maintaining Vehicular Ad-hoc Networks (VANETs) connectivity and coverage, especially, for applications gathering or disseminating non-safety information. In big cities with complex road network topology, huge number of costly RSUs must be deployed to collect data gathered by all moving vehicles. In this respect, several research works focusing on RSUs deployment, the so called coverage problem, have been proposed. The thriving challenge would be to (i) minimize as possible the number of used RSUs, which leads to reduce the deployment cost; and (ii) to maximize the coverage ratio. In this paper, we introduce a new spatio-temporal coverage scheme consisting of two main components, namely “mobility patterns mining” and “coverage computing”. The first one computes a sequential mobility patterns set of moving vehicles by mining their trajectories. whereas the second computes a minimal set of junctions, where RSUs have to be ideally placed. The performed thorough experiments show that our scheme outperforms its competitors in terms of cost as well as coverage ratio.
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Ben Chaabene, S., Yeferny, T., Ben Yahia, S. (2020). A Roadside Unit Placement Scheme for Vehicular Ad-hoc Networks. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2019. Advances in Intelligent Systems and Computing, vol 926. Springer, Cham. https://doi.org/10.1007/978-3-030-15032-7_52
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