Abstract
The least-cost multicast routing with delay constrained is an NP-Complete problems, to deal with which, a Multi-Agent Immune Clonal Selection Algorithm based multicast routing (MAICSA) is proposed in this paper. MAICSA combines the characteristic of Multi-Agent with the search strategy of Immune Clonal Selection Algorithm. To compare with the conventional Genetic Algorithm (GA), MAICSA overcomes the most serious drawbacks, such as slow convergence rate and “prematurity”. The experimental results show that MAICSA has faster astringency and higher precision than traditional GA, MAGA (Multi-Agent multicast routing based on Genetic Algorithm) and MAIA (Multi-Agent multicast routing based on Immune Algorithm).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Parsa, M.: An interactive algorithm for delay-constrained minimum-cost multicasting. IEEE/ACM Trans. on Networking 6(4), 461–474 (1998)
Chen, G.-L., et al.: Genetic Algorithm and Its Application. People’s Posts and Telecommunications Press, Beijing (1996)
Liu, Y.: Multicast routing algorithms computer networks [PhD dissertation]. Xidian University, Xi’an (2000)
Wang, X.-H., Wang, G.-X.: A multicast routing approach with delay constrained minimum cost based on genetic algorithm. Journal of China Institute of Communications 23(3), 112–117 (2002)
Shi, J., Zou, L., Dong, T.-L., Zhao, E.-D.: The Application of Genetic Algorithm in Multicast Routing. Acta Electronic Sinica 28(5), 88–89 (2000)
Jiao, L., Wang, L.: A novel genetic algorithm based on immune. IEEE Trans. on System, Man, and Cybernetics—Part A 30, 1–10 (2000)
Du, H.-F., Jiao, L.-C., et al.: Immune clonal selection algorithm and evolutionary algorithms. In: 2003 10th International Conference on Artificial Intelligence, Progress of Artificial Intelligence in China, pp. 694–699 (2003)
Jiao, L.-c., Du, H.-f.: The prospect of the artificial immune system. Acta Electronica Sinica 31(10), 1540–1548 (2003)
Singh, M.P.: Multi-agent system: A theoretical framework for intention, know-how and communication. Springer, Berlin (1944)
Zhong, W.-C., Liu, J., Xue, M.-Z., Jiao, L.-C.: A Multi-Agent Genetic Algorithm for Global Numerical Optimization. IEEE Trans. System, Man and Cybernetics—Part B 34(2), 1128–1141 (2004)
Liu, J., Zhong, W.-C., Jiao, L.-C.: A multiagent evolutionary algorithm for constraint satisfaction problems. IEEE Trans. Syst., Man, and Cybern. B 36(1), 54–73 (2006)
Jiao, L.-C., Liu, J., Zhong, W.-C.: An organizational coevolutionary algorithm for classification. IEEE Trans. Evol. Comput. 10(1), 67–80 (2006)
Waxman, B.M.: Routing of multiple connections. IEEE Journal of Selected Areas in Communications 6(9), 1617–1622 (1988)
Liu, Y.: The Multi-Agent Multicast Routing Algorithm based on Immune Clonal Computation. [MS dissertation]. Xidian University, Xi’an (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, F., Liu, Y., Chen, X., Wang, Js. (2006). Multi-Agent Immune Clonal Selection Algorithm Based Multicast Routing. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_39
Download citation
DOI: https://doi.org/10.1007/11881223_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45907-1
Online ISBN: 978-3-540-45909-5
eBook Packages: Computer ScienceComputer Science (R0)