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: A time domain approach," Tech. report 97-108, ESAT-SISTA, K.U.Leuven,
Leuven, Belgium, 15 pp., Nov. 1997.
Abstract
In this report a new fast time domain approach for the identification 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 statistic moments. Since the
identification of a general MMPP is time consuming because of the large
computational requirements, a
circulant MMPP is used to
reduce the computational cost. A circulant MMPP is an MMPP with a circulant
transition matrix. The main advantages of this approach are the avoidance of
inverse eigenvalue problem and the decoupling of the two statistic moments.
Since ATM-traffic is highly correlated one can expect slowly decaying
autocorrelations, which slows down the time domain identification. Therefore
the autocorrelation is rewritten as a sum of exponentials using
subspace-identification for stochastic linear time invariant systems. The
identification of the second order statistics is decoupled from the first order
statistics and uses 0/1 knapsack solvers and unconstrained optimisation.
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BibTeX
@techreport{VanDeC:97-108,
author = {Van Gestel, Tony and De Cock, Katrien and Jans, Raf and De
Schutter, Bart and Degraeve, Zeger and De Moor, Bart},
title = {Discrete Stochastic Modelling of {ATM}-Traffic with Circulant
Transition Matrices: {A} Time Domain Approach},
number = {97-108},
institution = {ESAT-SISTA, K.U.Leuven},
address = {Leuven, Belgium},
month = nov,
year = {1997}
}