Abstract
The advancement of network induces great demands on a series of applications such as the multicast routing. This paper firstly makes a brief review on the algorithms in solving routing problems. Then it proposes a novel algorithm called the distance complete ant colony system (DCACS), which is aimed at solving the multicast routing problem by utilizing the ants to search for the best routes to send data packets from a source node to a group of destinations. The algorithm bases on the framework of the ant colony system (ACS) and adopts the Prim’s algorithm to probabilistically construct a tree. Both the pheromone and heuristics influence the selection of the nodes. The destination nodes in the multicast network are given priority in the selection by the heuristics and a proper reinforcement proportion to the destination nodes is studied in the case experiments. Three types of heuristics are tested, and the results show that a modest heuristic reinforcement to the destination nodes can accelerate the convergence of the algorithm and achieve better results.
This work was supported by NSFC Joint Fund with Guangdong, Key Project No. U0835002, NSF of China Project No.60573066 and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry, P.R. China.
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Hu, XM., Zhang, J., Zhang, LM. (2009). Swarm Intelligence Inspired Multicast Routing: An Ant Colony Optimization Approach. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2009. Lecture Notes in Computer Science, vol 5484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01129-0_6
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DOI: https://doi.org/10.1007/978-3-642-01129-0_6
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