Multiobjective algorithms to optimize broadcasting parameters in mobile Ad-hoc networks

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Show simple item record Pérez, Ramón Luque, Cristóbal Cervantes, Alejandro Isasi, Pedro 2009-04-20T07:37:29Z 2009-04-20T07:37:29Z 2007-09
dc.identifier.bibliographicCitation IEEE Congress on Evolutionary Computation, 2007. CEC 2007. p. 3142-3149
dc.identifier.isbn 978-1-4244-1339-3
dc.description Congress on Evolutionary Computation. Singapore, 25-28 September 2007
dc.description.abstract A mobile adhoc network (MANETs) is a self-configuring network of mobile routers (and associated hosts). The routers tend to move randomly and organize themselves arbitrarily; thus, the network's wireless topology may change fast and unpredictably. Nowadays, these networks are having a great influence due to the fact that they can create networks without a specific infrastructure. In MANETs message broadcasting is critical to network existence and organization. The broadcasting strategy in MANETs can be optimized by defining a multiobjective problem whose inputs are the broadcasting algorithm's parameters and whose objectives are: reaching as many stations as possible, minimizing the network utilization, and reducing the makespan. The network can be simulated to obtain the expected response to a given set of parameters. In this paper, we face this multiobjective problem with two algorithms: Multiobjective Particle Swarm Optimization and ESN (Evolution Strategy with NSGAII). Both algorithms are able to find an accurate approximation to the Pareto optimal front that is the solution of the problem. ESN improves the results of MOPSO in terms of the set coverage and hypervolume metrics used for comparison.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.rights © IEEE
dc.title Multiobjective algorithms to optimize broadcasting parameters in mobile Ad-hoc networks
dc.type conferenceObject
dc.type bookPart
dc.subject.eciencia Informática
dc.identifier.doi 10.1109/CEC.2007.4424873
dc.rights.accessRights openAccess
dc.relation.eventdate 25-28 September 2007
dc.relation.eventplace Singapore
dc.relation.eventtitle Congress on Evolutionary Computation
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 3142
dc.identifier.publicationlastpage 3149
dc.identifier.publicationtitle IEEE Congress on Evolutionary Computation, 2007. CEC 2007
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