The advantage of indices of dispersion in queueing approximations

A recent robust queueing approximation for open queueing networks exploits partial characterizations of each arrival process by its rate and index of dispersion for counts (IDC), which is a scaled version of the variance–time curve. Even though only means and variances (as functions of time) are involved, we show that the IDC provides a basis for more accurate approximations than traditional two-moment partial characterizations. For the $GI∕GI∕1$ queue, this approach applied to the arrival and service processes fully characterizes the model.