Variability functions for parametric-decomposition approximations of queueing networks

We propose an enhancement to the parametric-decomposition method for calculating approximate steady-state performance measures of open queueing networks with non-Poisson arrival processes and nonexponential service-time distributions. Instead of using a variability parameter c a 2 for each arrival process, we suggest using a variability function c a 2 \rho, 0 a 2 \rho should be 0 for \rho near 0 or 1, but c a 2 \rho can assume arbitrarily large values for appropriate intermediate \rho. We present a full network algorithm with variability functions, showing that the idea is implementable. We also show how simulations of single queues can be effectively exploited to determine variability functions for difficult external arrival processes.

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