TY - JOUR

T1 - Methodology for traffic modeling using two-state Markov-Modulated Bernoulli Process

AU - Ng, C. H.

AU - Yuan, L.

AU - Fu, W.

AU - Zhang, L.

PY - 1999/8/25

Y1 - 1999/8/25

N2 - In this paper, we systematically present the methodology of modeling bursty traffic sources using the 2-state Markov Modulated Bernoulli Process (called MMBP-2). The technique used can be easily extended to an m-state MMBP though the numerical calculation is complicated. We first defined the parameters of the model and some processes associated with it, and subsequently examined the queue length distribution of an infinite buffer driven by an MMBP-2 with batch arrivals. We next looked at the case where the same buffer is fed by a group of two identical MMBP-2 sources. Instead of deriving the queue length expression, we cast the problem in the framework of the previous case and made use of the previous results with some modification. Lastly, we looked at the case of a finite buffer driven by two MMBP-2 sources with different parameters. We formulated the queue length solution in the framework of Markov theory and calculated the Cell Loss Probability (CLP) for this case.

AB - In this paper, we systematically present the methodology of modeling bursty traffic sources using the 2-state Markov Modulated Bernoulli Process (called MMBP-2). The technique used can be easily extended to an m-state MMBP though the numerical calculation is complicated. We first defined the parameters of the model and some processes associated with it, and subsequently examined the queue length distribution of an infinite buffer driven by an MMBP-2 with batch arrivals. We next looked at the case where the same buffer is fed by a group of two identical MMBP-2 sources. Instead of deriving the queue length expression, we cast the problem in the framework of the previous case and made use of the previous results with some modification. Lastly, we looked at the case of a finite buffer driven by two MMBP-2 sources with different parameters. We formulated the queue length solution in the framework of Markov theory and calculated the Cell Loss Probability (CLP) for this case.

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U2 - 10.1016/S0140-3664(99)00114-0

DO - 10.1016/S0140-3664(99)00114-0

M3 - Article

AN - SCOPUS:0032685568

VL - 22

SP - 1266

EP - 1273

JO - Computer Communications

JF - Computer Communications

SN - 0140-3664

IS - 13

ER -