Information dissemination in VANETs: deployment strategies for maximizing coverage

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/9897

dc.contributor	Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.contributor	Universitat Politècnica de Catalunya. CNDS - Xarxes de Computadors i Sistemes Distribuïts
dc.contributor.author	Trullols Cruces, Óscar
dc.contributor.author	Barceló Ordinas, José María
dc.contributor.author	Fiore, Marco
dc.contributor.author	Casetti, Claudio
dc.contributor.author	Chiasserini, Carla-Fabiana
dc.date	2009
dc.identifier.citation	Trullols, O. [et al.]. Information dissemination in VANETs: deployment strategies for maximizing coverage. A: Euro-NF Workshop on Wireless and Mobility. "6th. Euro-NF Workshop on Wireless and Mobility in the Network of the Future". Stresa, Lago Maggiore: 2009, p. 1-6.
dc.identifier.uri	http://hdl.handle.net/2117/9897
dc.language.iso	eng
dc.relation	http://www.tlc.polito.it/WWM2009/Euro-NF_WWM09/Home.html
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subject	Vehicular ad hoc networks
dc.subject	VANET
dc.subject	Xarxes ad hoc
dc.title	Information dissemination in VANETs: deployment strategies for maximizing coverage
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	We consider that a given number of Dissemination Points (DPs) have to be deployed for disseminating information to vehicles travelling in an urban area. We formulate our problem as a Maximum Coverage Problem (MCP) so as to maximize the number of vehicles that get in contact with the DPs. Since the MCP is NP-hard, we solve it though heuristic algorithms. Evaluation of the proposed solutions in a realistic urban environment shows how knowledge of vehicular mobility plays a major role in achieving an optimal coverage of mobile users, and that simple heuristics provide near-optimal results even in large-scale scenarios.
dc.description.abstract	Peer Reviewed

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