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The Intelligent Agent-Based Control of Service Processing Capacity

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2003)

Abstract

The paper presents new approach to processing capacity protection in the service system with multiple server units. In the integrated service communication networks an important problem is to implement call admission control and routing so as to optimally use the network resources. We assumed reality of several classes of jobs and tried to preserve an amount of processing capacity for high priority jobs that can arrive in a burst. In parallel, current low priority jobs were processed with continuous regulation of servers load. Simulation results showed rapid adaptation and good balancing around the predetermined maximum processing level. Inspiration was found in the paradigm of software agent technology and potential advantages appearing when applied in telecommunication network. Main characteristic of the usage of intelligent agent is the opportunity to permanently transfer adaptation regarding one or more parameters following optimal and requested policy.

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References

  1. Watkins, C.J.C.H., Dayan, P.: Q-learning. Machine Learning 8, 55–68 (1992)

    Google Scholar 

  2. Sutton, R.S., Barto, A.G.: Reinforcement Learning – An Introduction. MIT Press, Cambridge (1998)

    Google Scholar 

  3. Bertsekas, D.P., Tsitsiklis, J.N.: Neuro-Dynamic Programming. Athena Scientific, MIT, Belmont, Massachusetts (1996)

    MATH  Google Scholar 

  4. Atlasis, A.F., Vasilakos, A.V.: The Use of Reinforcement Learning Algorithms in Traffic Control of High Speed Networks. In: Proceedings European Symposium on Intelligent Techniques, Aachen, Germany, pp. 283–288 (2000)

    Google Scholar 

  5. Marbach, P., Mihatsch, O., Tsitsiklis, J.N.: Call Admission Control and Routing in Integrated Service Networks Using Neuro-Dynamic Programming. IEEE Journal on Selected Areas in Communications 18(2), 197–208 (2000)

    Article  Google Scholar 

  6. Kunstic, M., Jevtic, D., Sablic, D.: Self-trained agents optimize communication service by intelligent selection. In: Proc. KES 2000, Brigthon, England, vol. 2, pp. 687–690 (2000)

    Google Scholar 

  7. Jevtic, D., Kunstic, M., Cunko, K.: Traffic-Dependent Routing Based on Selfadaptation. Frontiers in Artificial Intelligence and Applications 82(Part 1), 184–188 (2002) ISSN: 0922-6389

    Google Scholar 

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© 2003 Springer-Verlag Berlin Heidelberg

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Jevtic, D., Kunstic, M., Jerkovic, N. (2003). The Intelligent Agent-Based Control of Service Processing Capacity. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_92

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  • DOI: https://doi.org/10.1007/978-3-540-45226-3_92

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40804-8

  • Online ISBN: 978-3-540-45226-3

  • eBook Packages: Springer Book Archive

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