On the accuracy of the opc approximation for a symmetric overflow loss model

Abstract

The overflow priority classification approximation (OPCA) and Erlang's fixed-point approximation (EFPA) are distinct methods for estimating blocking probabilities in overflow loss networks. Mounting numerical evidence has indicated that OPCA provides superior accuracy than EFPA in many circumstances. Furthermore, it has been proven that P EFPA ≤ P OPCA for a symmetric overflow loss network called the distributed server model, where P x is the blocking probability estimate yielded by approximation x {EFPA, OPCA}. The distributed server model is an ideal "proving ground" because the exact blocking probability, P exact, can be calculated with the Erlang B formula, yet the state dependencies cau..