Discrete stochastic modelling of ATM-traffic with circulant transition matrices


Reference:

T. Van Gestel, K. De Cock, R. Jans, B. De Schutter, Z. Degraeve, and B. De Moor, "Discrete stochastic modelling of ATM-traffic with circulant transition matrices," Mathematical Theory of Networks and Systems (Proceedings of the MTNS-98 Symposium, held in Padova, Italy, July 1998) (A. Beghi, L. Finesso, and G. Picci, eds.), Padova, Italy: Il Poligrafo, pp. 891-894, 1998.

Abstract:

In this paper a new approach to the modelling of ATM-traffic is proposed. The traffic is measured and characterised by its first and second order statistic moments. A Markov Modulated Poisson Process (MMPP) is used to capture the information in these two stochastic moments. Instead of a general MMPP, a circulant MMPP is used to reduce the computational cost. A circulant MMPP (CMMPP) is an MMPP with a circulant transition matrix. The main advantages of this approach are that the eigenvalue decomposition is a Fast Fourier Transform and that the optimisation towards the two stochastic moments is decoupled. Based on these properties, a fast time domain identification algorithm is developed.

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Bibtex entry:

@inproceedings{VanDeC:97-109,
author={T. {V}an Gestel and K. {D}e Cock and R. Jans and B. {D}e Schutter and Z. Degraeve and B. {D}e Moor},
title={Discrete stochastic modelling of {ATM}-traffic with circulant transition matrices},
booktitle={Mathematical Theory of Networks and Systems \normalfont(Proceedings of the MTNS-98 Symposium, held in Padova, Italy, July 1998)},
editor={A. Beghi and L. Finesso and G. Picci},
publisher={Padova, Italy: Il Poligrafo},
pages={891--894},
year={1998}
}


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