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Ant Colony Optimization for Multi-Objective Multicast Routing

by Ahmed Y. Hamed, Monagi H. Alkinani, M. R. Hassan

1 Department of Computer Science, Faculty of Computers and Information, Sohag University, Sohag, 82524, Egypt.
2 Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia.
3 Department of Mathematics and Computer Science, Faculty of Science, Aswan University, Aswan, 81528, Egypt.

* Corresponding Author: M. R. Hassan. Email: email.

Computers, Materials & Continua 2020, 63(3), 1159-1173. https://doi.org/10.32604/cmc.2020.09176

Abstract

In the distributed networks, many applications send information from a source node to multiple destination nodes. To support these applications requirements, the paper presents a multi-objective algorithm based on ant colonies to construct a multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results prove the proposed algorithm outperforms a recently published Multi-objective Multicast Algorithm specially designed for solving the multicast routing problem. Also, it is able to find a better solution with fast convergence speed and high reliability.

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APA Style
Y. Hamed, A., H. Alkinani, M., R. Hassan, M. (2020). Ant colony optimization for multi-objective multicast routing. Computers, Materials & Continua, 63(3), 1159-1173. https://doi.org/10.32604/cmc.2020.09176
Vancouver Style
Y. Hamed A, H. Alkinani M, R. Hassan M. Ant colony optimization for multi-objective multicast routing. Comput Mater Contin. 2020;63(3):1159-1173 https://doi.org/10.32604/cmc.2020.09176
IEEE Style
A. Y. Hamed, M. H. Alkinani, and M. R. Hassan, “Ant Colony Optimization for Multi-Objective Multicast Routing,” Comput. Mater. Contin., vol. 63, no. 3, pp. 1159-1173, 2020. https://doi.org/10.32604/cmc.2020.09176

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cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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