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Soft Computing in Communications pp 175–200Cite as

Solving the QoS Multicast Routing Problems Using Genetic Algorithms

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 136))

Abstract

Multicasting has been viewed as a viable means with high potential of improving service efficiency and quality in distributing multimedia information through networks. Because of its strategic importance, many interesting research topics have been articulated. One of such emerging topics is the multicast routing problem. This study explores the use of genetic algorithms (GAs) for solving the multicast routing problems when multiple quality of services (QoS) requirements are presented; compares for a small network the performance of two GAs with different representation schemes and constraints handling methods; and examines for a small- and a medium- size networks the effect of population sizes and mutation probabilities on solution quality. Our simulation results indicate that it is critical to select a suitable representation method and a set of appropriate parameters in order to obtain good performance.

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Authors and Affiliations

  1. School of Information Sciences and Technology, The Pennsylvania State University, 001 Thomas Building, University Park, PA, 16802, USA

    Qijun Gu & Chao-Hsien Chu

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  1. Qijun Gu
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  2. Chao-Hsien Chu
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© 2004 Springer-Verlag Berlin Heidelberg

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Gu, Q., Chu, CH. (2004). Solving the QoS Multicast Routing Problems Using Genetic Algorithms. In: Soft Computing in Communications. Studies in Fuzziness and Soft Computing, vol 136. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45090-0_9

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  • DOI: https://doi.org/10.1007/978-3-540-45090-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53623-6

  • Online ISBN: 978-3-540-45090-0

  • eBook Packages: Springer Book Archive

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