Discrete stochastic modelling of ATM-traffic with circulant transition matrices
Tony Van Gestel, Katrien De Cock, Raf Jans, Bart De Schutter, Zeger Degraeve, Bart De Moor · Lirias · 1998
In this paper a new approach to the modelling of ATMtraffic 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. 1 Introduction Asynchronous Transfer Mode (ATM) is a protocol for packet switched broadband ISDN networks. Its main characteristic is that it combines the advantages of the classic circuit mode and packet mode traffic. Therefore ATM uses the principle of statistical multiplexing, which is very efficient...