Abstract
Markov modulated fluid models are widely used in modelling communications and computer systems. In the AMS (Annick, Mitra, Sohndi) model, heterogeneous, bursty sources modeled by multidimensional Markov processes are superimposed or multiplexed together to drive a fluid buffer. The performance of the system is measured by the steady state probability that the buffer exceeds a high level. The exact solution to this problem derived by AMS requires too much computation to be used on-line. Here we derive an upper bound for the above probability which is fast to compute and accurate enough for practical use.
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