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Mathematical Problems in Engineering
Volume 2013, Article ID 432686, 13 pages
Research Article

Minimum Cost Multicast Routing Using Ant Colony Optimization Algorithm

Department of Computer Science, Sun Yat-sen University, Key Laboratory of Intelligent Sensor Networks, Ministry of Education, Key Laboratory of Software Technology, Education Department of Guangdong Province, Guangzhou 510006, Guangdong Province, China

Received 7 February 2013; Accepted 18 April 2013

Academic Editor: Yuping Wang

Copyright © 2013 Xiao-Min Hu and Jun Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Multicast routing (MR) is a technology for delivering network data from some source node(s) to a group of destination nodes. The objective of the minimum cost MR (MCMR) problem is to find an optimal multicast tree with the minimum cost for MR. This problem is NP complete. In order to tackle the problem, this paper proposes a novel algorithm termed the minimum cost multicast routing ant colony optimization (MCMRACO). Based on the ant colony optimization (ACO) framework, the artificial ants in the proposed algorithm use a probabilistic greedy realization of Prim’s algorithm to construct multicast trees. Moving in a cost complete graph (CCG) of the network topology, the ants build solutions according to the heuristic and pheromone information. The heuristic information represents problem-specific knowledge for the ants to construct solutions. The pheromone update mechanisms coordinate the ants’ activities by modulating the pheromones. The algorithm can quickly respond to the changes of multicast nodes in a dynamic MR environment. The performance of the proposed algorithm has been compared with published results available in the literature. Results show that the proposed algorithm performs well in both static and dynamic MCMR problems.