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Route Reinforcement for Efficient QoS Routing Based on Ant Algorithm

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Information Networking. Networking Technologies for Broadband and Mobile Networks (ICOIN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3090))

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Abstract

In this paper, we present a new method to calculate reinforcement value in QoS routing algorithm for real-time multimedia based on Ant algorithm to efficiently and effectively reinforce ant-like mobile agents to find the best route toward destination in a network. Simulation results show that the proposed method realizes QoS routing more efficiently and more adaptively than those of the existing method thereby providing better solutions for the best route selection.

This work was supported by the Brain Korea 21 Project in 2003.

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References

  1. Zhang, S., Liu, Z.: A QoS Routing Algorithm Based on Ant Algorithm. In: 25th Annual IEEE Conference on Local Computer Networks, pp. 574–578 (2000)

    Google Scholar 

  2. Dorigo, M., Di Caro, G.: AntNet: Distributed Stigmergetic Control for Communications Networks. Journal of Artificail Intelligence Research 9, 317–365 (1999)

    Google Scholar 

  3. Quadros, G., Monteiro, E., Boavida, F.: A QoS Metric for Packet Networks. In: Proc. of SPIE International Symposium on Voice, Video, and Data Communications Conference (1998)

    Google Scholar 

  4. Dorigo, M., Gambardella, L.M.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Trans. on Evolutionary Computation, 53–66 (1997)

    Google Scholar 

  5. Stutzle, T., Dorigo, M.: ACO algorithms for the quadratic assignment problem. New Ideas in Optimization, pp. 33–50. McGraw Hill, New York (1999)

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  6. Chu, C., Gu, J., Hou, X., Gu, Q.: A Heuristic Ant Algorithm for Solving QoS Multicast Routing Problem. In: Proceedings of the 2002 Congress on Evolutionary Computatioin, CEC 2002, vol. 2, pp. 12–17 (2002)

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© 2004 Springer-Verlag Berlin Heidelberg

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Oh, J.S., Bae, Si., Ahn, Jh., Kang, S. (2004). Route Reinforcement for Efficient QoS Routing Based on Ant Algorithm. In: Kahng, HK., Goto, S. (eds) Information Networking. Networking Technologies for Broadband and Mobile Networks. ICOIN 2004. Lecture Notes in Computer Science, vol 3090. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25978-7_35

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  • DOI: https://doi.org/10.1007/978-3-540-25978-7_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23034-2

  • Online ISBN: 978-3-540-25978-7

  • eBook Packages: Springer Book Archive

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