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Neural Approximation of Resource Allocation Functions in Multiservice Access Multiplexers

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Soft Computing in Communications

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

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Abstract

In an access node to a multiservice network (e.g., a base station in an integrated services cellular wireless network the hub station in a double hop satellite system, or the Optical Line Terminal (OLT) in a broadband Passive Optical Network (PON)), the output link bandwidth is adaptively assigned to different users, and dynamically shared between guaranteed bandwidth traffic and asynchronous traffic types. The bandwidth allocation is effected by an admission controller, whose goal is to minimize the refusal rate of bandwidth reservation requests as well as the loss probability of cells queued in a finite buffer. Optimal admission control strategies are approximated by means of backpropagation feedforward neural networks, acting on the embedded Markov chain of the guaranteed bandwidth traffic dynamics; the neural networks operate in conjunction with a higher level bandwidth allocation controller, which performs a stochastic optimization algorithm. The case of unknown, slowly varying input rates is explicitly considered. Numerical results are presented that evaluate the approximation and the ability to adapt to parameter variations.

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Authors and Affiliations

  1. Department of Communications, Computer and Systems Science, DIST-University of Genova, Via Opera Pia 13, 16145, Genova, Italy

    Franco Davoli

  2. Datasiel S.p.A., Via Merano 22, 16154, Genova, Italy

    Piergiulio Maryni

Authors
  1. Franco Davoli
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  2. Piergiulio Maryni
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© 2004 Springer-Verlag Berlin Heidelberg

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Davoli, F., Maryni, P. (2004). Neural Approximation of Resource Allocation Functions in Multiservice Access Multiplexers. 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_1

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  • DOI: https://doi.org/10.1007/978-3-540-45090-0_1

  • 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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