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.
Downloads
- Corresponding technical report:
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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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