Markov modüleli girdilerle beslenen bir eşzamansız aktarım modu çoğullayıcısının başarım analizi

Asynchronous Transfer Mode (ATM) networks have inputs which consist of superpositions of correlated cell streams. Markov modulated processes are commonly used to characterize this correlation. The first step through gaining an analytical insight in the performance issues of an ATM network is the analysis of a single channel. One objective of this study is the performance analysis of an ATM multiplexer whose input İs a Markov modulated periodic arrival process. Based on the transient behavior of the nD/D/l queue, we present an approximate method to compute the queue length distribution accurately. The method reduces to the solution of a linear differential equation with variable coefficients. Another general traffic model is the Markov Modulated Poisson Process (MMPP). We employ Fade approximations in transform domain for the deterministic service time distribution in an MMPP/D/1 queue so as to compute the distribution of the buffer occupancy. For both models, we also provide algorithms for analysis in the case of finite queue capacities and for computation of effective bandwidth. Keywords: ATM, statistical multiplexing, fluid models, Markov modulated processes, traffic control in ATM networks, effective bandwidth.