000065258 001__ 65258
000065258 005__ 20200117211601.0
000065258 0247_ $$2doi$$a10.3390/app8010086
000065258 0248_ $$2sideral$$a104192
000065258 037__ $$aART-2018-104192
000065258 041__ $$aeng
000065258 100__ $$0(orcid)0000-0003-1044-7335$$aFogue, M.
000065258 245__ $$aImproving Roadside Unit deployment in vehicular networks by exploiting genetic algorithms
000065258 260__ $$c2018
000065258 5060_ $$aAccess copy available to the general public$$fUnrestricted
000065258 5203_ $$aVehicular networks make use of the Roadside Units (RSUs) to enhance the communication capabilities of the vehicles in order to forward control messages and/or to provide Internet access to vehicles, drivers and passengers. Unfortunately, within vehicular networks, the wireless signal propagation is mostly affected by buildings and other obstacles (e.g., urban fixtures), in particular when considering the IEEE 802.11p standard. Therefore, a crowded RSU deployment may be required to ensure vehicular communications within urban environments. Furthermore, some applications, notably those applications related to safety, require a fast and reliable warning data transmission to the emergency services and traffic authorities. However, communication is not always possible in vehicular environments due to the lack of connectivity even employing multiple hops. To overcome the signal propagation problem and delayed warning notification time issues, an effective, smart, cost-effective and all-purpose RSU deployment policy should be put into place. In this paper, we propose the genetic algorithm for roadside unit deployment (GARSUD) system, which uses a genetic algorithm that is capable of automatically providing an RSU deployment suitable for any given road map layout. Our simulation results show that GARSUD is able to reduce the warning notification time (the time required to inform emergency authorities in traffic danger situations) and to improve vehicular communication capabilities within different density scenarios and complexity layouts.
000065258 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/TEC2014-52690-R
000065258 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000065258 590__ $$a2.217$$b2018
000065258 591__ $$aPHYSICS, APPLIED$$b66 / 148 = 0.446$$c2018$$dQ2$$eT2
000065258 591__ $$aCHEMISTRY, MULTIDISCIPLINARY$$b88 / 172 = 0.512$$c2018$$dQ3$$eT2
000065258 591__ $$aMATERIALS SCIENCE, MULTIDISCIPLINARY$$b151 / 293 = 0.515$$c2018$$dQ3$$eT2
000065258 592__ $$a0.379$$b2018
000065258 593__ $$aComputer Science Applications$$c2018$$dQ1
000065258 593__ $$aEngineering (miscellaneous)$$c2018$$dQ1
000065258 593__ $$aProcess Chemistry and Technology$$c2018$$dQ1
000065258 593__ $$aInstrumentation$$c2018$$dQ1
000065258 593__ $$aMaterials Science (miscellaneous)$$c2018$$dQ1
000065258 593__ $$aFluid Flow and Transfer Processes$$c2018$$dQ1
000065258 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000065258 700__ $$0(orcid)0000-0001-7657-0075$$aSanguesa, J.A.
000065258 700__ $$aMartinez, F.J.
000065258 700__ $$aMarquez-Barja, J.M.
000065258 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDepartamento de Informática e Ingeniería de Sistemas$$cLenguajes y Sistemas Informáticos
000065258 773__ $$g8, 1 (2018), 010086 [21 pp]$$pAppl. sci.$$tApplied Sciences (Switzerland)$$x2076-3417
000065258 8564_ $$s1325520$$uhttp://zaguan.unizar.es/record/65258/files/texto_completo.pdf$$yVersión publicada
000065258 8564_ $$s109793$$uhttp://zaguan.unizar.es/record/65258/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000065258 909CO $$ooai:zaguan.unizar.es:65258$$particulos$$pdriver
000065258 951__ $$a2020-01-17-21:12:31
000065258 980__ $$aARTICLE