Multi-Objective Multicast Routing based on Ant Colony Optimization

Authors:
Diego Pinto;Benjamín Barán;Ramón Fabregat
Affiliations:
National Computing Center, National University of Asuncion-Paraguay and Science and Technology Department, Catholic University of Asunción -Paraguay, {dpinto, bbaran}@cnc.una.py;National Computing Center, National University of Asuncion-Paraguay and Science and Technology Department, Catholic University of Asunción -Paraguay, {dpinto, bbaran}@cnc.una.py;Institut d'Informàtica i Aplicacions-Universitat of Girona. Girona, Spain, {ramon.fabregat}@udg.es
Venue:
Proceedings of the 2005 conference on Artificial Intelligence Research and Development
Year:
2005

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Abstract

This work presents a new multiobjective algorithm based on ant colonies, which is used in the construction of the multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes cost of the multicast tree, average delay and maximum end-to-end delay. In this way, a set of optimal solutions, know as Pareto set, is calculated in only one run of the algorithm, without a priori restrictions. The proposed algorithm was inspired in a Multi-objective Ant Colony System (MOACS). Experimental results prove the proposed algorithm outperforms a recently published Multiobjective Multicast Algorithm (MMA), specially designed for solving the multicast routing problem.