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Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Computación Evolutiva y Redes Neuronales (EVANNAI)es
dc.contributor.authorSegura, Carlos
dc.contributor.authorCervantes, Alejandro
dc.contributor.authorNebro, Antonio J.
dc.contributor.authorJaraíz-Simón, María Dolores
dc.contributor.authorSegredo, Eduardo
dc.contributor.authorGarcía-Rodríguez, Sandra
dc.contributor.authorLuna, Francisco
dc.contributor.authorGómez-Pulido, Juan A.
dc.contributor.authorMiranda, Gara
dc.contributor.authorLuque, Cristóbal
dc.contributor.authorAlba, Enrique
dc.contributor.authorVega-Rodríguez, Miguel A.
dc.contributor.authorLeón, Coromoto
dc.contributor.authorGalván, Inés M.
dc.date.accessioned2012-12-14T10:12:55Z
dc.date.available2012-12-14T10:12:55Z
dc.date.issued2009
dc.descriptionProceeding of: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009
dc.description.abstractThis work presents the application of a parallel coopera- tive optimization approach to the broadcast operation in mobile ad-hoc networks (manets). The optimization of the broadcast operation im- plies satisfying several objectives simultaneously, so a multi-objective approach has been designed. The optimization lies on searching the best configurations of the dfcn broadcast protocol for a given manet sce- nario. The cooperation of a team of multi-objective evolutionary al- gorithms has been performed with a novel optimization model. Such model is a hybrid parallel algorithm that combines a parallel island- based scheme with a hyperheuristic approach. Results achieved by the algorithms in different stages of the search process are analyzed in order to grant more computational resources to the most suitable algorithms. The obtained results for a manets scenario, representing a mall, demon- strate the validity of the new proposed approach.
dc.description.sponsorshipThis work has been supported by the ec (feder) and the Spanish Ministry of Education and Science inside the ‘Plan Nacional de i+d+i’ (tin2005-08818-c04) and (tin2008-06491-c04-02). The work of Gara Miranda has been developed under grant fpu-ap2004-2290.
dc.description.statusPublicado
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationEvolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009. Proceedings. Springer, 2009, pp. 305-319
dc.identifier.doi10.1007/978-3-642-01020-0_26
dc.identifier.isbn978-3-642-01019-4
dc.identifier.issn0302-9743
dc.identifier.publicationfirstpage305
dc.identifier.publicationlastpage319
dc.identifier.publicationtitleaEvolutionary Multi-Criterion Optimization: 5th International Conference, EMO 2009
dc.identifier.urihttps://hdl.handle.net/10016/16040
dc.language.isoeng
dc.publisherSpringer
dc.relation.eventdateApril 7-10, 2009
dc.relation.eventnumber5
dc.relation.eventplaceNantes, France
dc.relation.eventtitleInternational Conference, EMO 2009
dc.relation.ispartofseriesLecture notes in computer science, vol. 5467
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-642-01020-0_26
dc.rights© Springer-Verlag Berlin Heidelberg
dc.rights.accessRightsopen access
dc.subject.ecienciaInformática
dc.subject.otherMultiobjective evolutionary algorithms
dc.titleOptimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms
dc.typeconference paper*
dc.type.hasVersionAM*
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