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

Identifieur interne : 000B96 ( Main/Exploration ); précédent : 000B95; suivant : 000B97

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

Auteurs : Carlos Segura [Espagne] ; Alejandro Cervantes [Espagne] ; J. Nebro [Espagne] ; Dolores Jaraíz-Sim N ; Eduardo Segredo ; Sandra García [Espagne] ; Francisco Luna [Espagne] ; Antonio G Mez-Pulido ; Gara Miranda ; Crist Bal Luque [Espagne] ; Enrique Alba [Espagne] ; Ángel Vega-Rodríguez ; Coromoto Le N ; M. Galván [Espagne]

Source :

Lecture Notes in Computer Science [ 0302-9743 ] ; 2009.

RBID : ISTEX:1AC03B29BD633494A566F4BF8F86054CBF78BB46

Abstract

Abstract: This work presents the application of a parallel cooperative optimization approach to the broadcast operation in mobile ad-hoc networks (manets). The optimization of the broadcast operation implies 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 scenario. The cooperation of a team of multi-objective evolutionary algorithms 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, demonstrate the validity of the new proposed approach.

Url:

https://api.istex.fr/document/1AC03B29BD633494A566F4BF8F86054CBF78BB46/fulltext/pdf

DOI: 10.1007/978-3-642-01020-0_26

Affiliations:

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Le document en format XML

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<front><div type="abstract" xml:lang="en">Abstract: This work presents the application of a parallel cooperative optimization approach to the broadcast operation in mobile ad-hoc networks (manets). The optimization of the broadcast operation implies 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 scenario. The cooperation of a team of multi-objective evolutionary algorithms 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, demonstrate the validity of the new proposed approach.</div>
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Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms

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

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Abstract

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