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MulRoGA: A Multicast Routing Genetic Algorithm approach considering multiple objectives

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Abstract

We solve a multicast routing problem by means of a genetic algorithm (GA) without using multicast trees. The source-destination routes need to fulfill two conflicting objectives: maximization of the common links and minimization of the route sizes. The proposed GA can be characterized by its representation of network links and routes in a variable size multi-chromosome problem; local viability restrictions in order to generate the initial population and define variation operators; selection operators in order to choose the most promising individuals thus preserving diversity, and the fitness function in order to handle the conflicting multiple objectives. The proposed model is called a Multicast Routing Genetic Algorithm (MulRoGA). The model was tested on the 33-node European GÉANT WAN network backbone and three other networks (66-node, 100-node and 200-node) randomly generated using the Waxman model on a network topology generator BRITE. On considering each network, a number of solutions were found for changes in the size and node members of the multicast groups, and the source node. The results of the MulRoGA operation suggest a consistent and robust performance in the various cases including comparisons with the methods of unicast shortest path routing, shortest path tree routing (SPT), and simulated annealing (SA) heuristic.

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Authors and Affiliations

  1. Center of Informatics, Federal University of Pernambuco, Recife, Brazil

    Aluizio Fausto Ribeiro Araújo & Cícero Garrozi

Authors
  1. Aluizio Fausto Ribeiro Araújo
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  2. Cícero Garrozi
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Corresponding author

Correspondence to Aluizio Fausto Ribeiro Araújo.

Additional information

The authors were supported by the Brazilian Council for Scientific and Technological Development (CNPq).

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Araújo, A.F.R., Garrozi, C. MulRoGA: A Multicast Routing Genetic Algorithm approach considering multiple objectives. Appl Intell 32, 330–345 (2010). https://doi.org/10.1007/s10489-008-0148-5

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  • DOI: https://doi.org/10.1007/s10489-008-0148-5

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