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dc.creatorGutiérrez Reina, Danieles
dc.creatorSharma, Vishales
dc.creatorYou, Ilsunes
dc.creatorToral, S. L.es
dc.date.accessioned2018-07-23T11:19:12Z
dc.date.available2018-07-23T11:19:12Z
dc.date.issued2018
dc.identifier.citationGutiérrez Reina, D., Sharma, V., You, I. y Toral, S.L. (2008). Dissimilarity metric based on local neighboring information and genetic programming for data dissemination in vehicular ad hoc networks (VANETs). Sensors, 18 (2320), 1-18.
dc.identifier.issn1424-8220es
dc.identifier.urihttps://hdl.handle.net/11441/77519
dc.description.abstractThis paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data dissemination schemes, which use the relative Euclidean distance among vehicles to determine the retransmission probability. The novel dissimilarity metric is obtained by applying a metaheuristic genetic programming approach, which provides a formula that maximizes the Pearson Correlation Coefficient between the novel dissimilarity metric and the Euclidean metric in several representative VANET scenarios. Findings show that the obtained dissimilarity metric correlates with the Euclidean distance up to 8.9% better than classical dissimilarity metrics. Moreover, the obtained dissimilarity metric is evaluated when used in well-known data dissemination schemes, such as p-persistence, polynomial and irresponsible algorithm. The obtained dissimilarity metric achieves significant improvements in terms of reachability in comparison with the classical dissimilarity metrics and the Euclidean metric-based schemes in the studied VANET urban scenarios.es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofSensors, 18 (2320), 1-18.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectVANETses
dc.subjectGenetic programming;es
dc.subjectBroadcasting communicationses
dc.titleDissimilarity metric based on local neighboring information and genetic programming for data dissemination in vehicular ad hoc networks (VANETs)es
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería Electrónicaes
dc.relation.publisherversionhttp://www.mdpi.com/1424-8220/18/7/2320es
dc.identifier.doi10.3390/s18072320es
idus.format.extent18 p.es
dc.journaltitleSensorses
dc.publication.volumen18es
dc.publication.issue2320es
dc.publication.initialPage1es
dc.publication.endPage18es

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