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Improving Roadside Unit Deployment in Vehicular Networks by Exploiting Genetic Algorithms

iNiT Research Group, Computer Science and System Engineering Department, University of Zaragoza, Ciudad Escolar s/n, 44003 Teruel, Spain
IDLab—Faculty of Applied Engineering, University of Antwerp—imec, Groenenborgerlaan 171, 2020 Antwerp, Belgium
Author to whom correspondence should be addressed.
Appl. Sci. 2018, 8(1), 86;
Received: 18 November 2017 / Revised: 18 December 2017 / Accepted: 3 January 2018 / Published: 9 January 2018
Vehicular networks make use of the Roadside Units (RSUs) to enhance the communication capabilities of the vehicles in order to forward control messages and/or to provide Internet access to vehicles, drivers and passengers. Unfortunately, within vehicular networks, the wireless signal propagation is mostly affected by buildings and other obstacles (e.g., urban fixtures), in particular when considering the IEEE 802.11p standard. Therefore, a crowded RSU deployment may be required to ensure vehicular communications within urban environments. Furthermore, some applications, notably those applications related to safety, require a fast and reliable warning data transmission to the emergency services and traffic authorities. However, communication is not always possible in vehicular environments due to the lack of connectivity even employing multiple hops. To overcome the signal propagation problem and delayed warning notification time issues, an effective, smart, cost-effective and all-purpose RSU deployment policy should be put into place. In this paper, we propose the genetic algorithm for roadside unit deployment (GARSUD) system, which uses a genetic algorithm that is capable of automatically providing an RSU deployment suitable for any given road map layout. Our simulation results show that GARSUD is able to reduce the warning notification time (the time required to inform emergency authorities in traffic danger situations) and to improve vehicular communication capabilities within different density scenarios and complexity layouts. View Full-Text
Keywords: genetic algorithms; VANETs; vehicular networks; roadside units; RSU deployment genetic algorithms; VANETs; vehicular networks; roadside units; RSU deployment
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Fogue, M.; Sanguesa, J.A.; Martinez, F.J.; Marquez-Barja, J.M. Improving Roadside Unit Deployment in Vehicular Networks by Exploiting Genetic Algorithms. Appl. Sci. 2018, 8, 86.

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