What is it about?
The most significant elements of a vehicular ad hoc network (VANET), besides VANET-enabled vehicles, are roadside units (RSUs). The effectiveness of a VANET mainly depends on the density and location of these RSUs. Throughout the primary stages of VANET, it will not be potential to deploy a big number of RSUs either due to the low marketplace penetration of VANET enabled vehicles or due to the deployment price of RSUs. There is, therefore, a need to optimally place a limited number of RSUs in a specified area in order to accomplish maximum performance. In this paper, we present the well-known genetic algorithm based on RSU location to find an optimal or near optimal solution. We provide the basic simulation environment of this work OSM to download real map data, GatcomSUMO to generate car mobility, SUMO to simulate road traffic, veins model framework for running vehicular network simulations on Omnet++, Omnet++ to simulate realistic network and Matlab to build the algorithm in order to analyze the results.
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Why is it important?
The simulation scenario is based on the Hamra district of Beirut, Lebanon. Based on the genetic algorithm, our proposed RSU placement model demonstrates that an optimal RSU position that can enhance the reception of basic safety message (BSM) delivered from the vehicles, can be accomplished in a specified road-map layout.
Perspectives
n this paper, have proposed GA based RSU placementapproach, which is accomplished by automatically determiningthe optimal RSU position to enhance received BSM messagedelivery from vehicle in any specified roadmap layout, rang-ing from regular too difficult city map layouts. Simulationresults, based on realistic traces and map layouts, provethat geneticalgorithm- based RSU is able to maximize theBSM message in different map layouts, including complexscenarios, under different vehicular densities, as well as whena different number of RSUs needs to be deployed. Demonstratethat the GA based RSU location optimization successfullyselects RSU locations at dense vehicle flow locations
Dr. Mahmood A. Al-shareeda
Universiti Sains Malaysia
Read the Original
This page is a summary of: Towards the Optimization of Road Side Unit Placement Using Genetic Algorithm, November 2018, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/acit.2018.8672687.
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