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Communication Dans Un Congrès Année : 2015

An Optimized Roadside Units (RSU) Placement for Delay-Sensitive Applications in Vehicular Networks

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Over the last few years, a lot of applications have been developed for Vehicular Ad Hoc NETworks (VANETs) to exchange information between vehicles. However, VANET is basically a Delay Tolerant Network (DTN) characterized by intermittent connectivity, long delays and message losses especially in low density regions [1]. Thus, VANET requires the use of an infrastructure such as Roadside Units (RSUs) that permits to enhance the network connectivity. Nevertheless, due to their deployment cost, RSUs need to be optimally deployed. Hence, the main objective of this work is to provide an optimized RSUs placement for delay-sensitive applications in vehicular networks that improves the end-to-end application delay and reduces the deployment cost. In this paper, we first mathematically model the placement problem as an optimization problem. Then, we propose our novel solution called ODEL. ODEL is a two-steps technique that places RSUs only in useful locations and allows both vehicle-to-vehicle and vehicle-to-infrastructure communication: (i) the first step is comprehensive study that looks for the RSUs candidates locations based on connectivity information, and (ii) the second step uses genetic algorithm and Dijkstra algorithm to reduce the number of RSUs based on the deliverance time requirement and the deployment cost. We show the effectiveness of our solution for different scenarios in terms of applications delay (reduced by up to 84%) and algorithm efficiency (computation performance reduced by up to 79% and deployment cost reduced at least by up to 23%).
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hal-01401024 , version 1 (20-02-2020)

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Sara Mehar, Sidi-Mohammed Senouci, Ali Kies, Zoulikha Mekkakia Maaza. An Optimized Roadside Units (RSU) Placement for Delay-Sensitive Applications in Vehicular Networks. 12th Annual Ieee Consumer Communications and Networking Conference, 2015, New York, United States. pp.121-127, ⟨10.1109/CCNC.2015.7157957⟩. ⟨hal-01401024⟩
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