A new method to determine the queue length distribution at an ATM multiplexer

In this paper, we develop a simple analytical technique to determine P({Q>q}), the tail of the queue length distribution, at an ATM multiplexer. The ATM multiplexer is modeled as a fluid queue serving a large number of independent sources. Our method is based on the central limit theorem and the maximum variance approximation, and enables us to avoid the state explosion problem. The approach is quite general and not limited by a Markovian framework. We apply our analytical method to study the buffer behavior for various traffic sources such as multiplexed homogeneous and heterogeneous Markov modulated sources, sources that are correlated at multiple time scales, sources whose autocorrelation function exhibits heavy (sub-exponential) tail behavior, and sources generated from real MPEG-encoded video sequences.