A Recursive Algorithm for Gamma Mixture Models

Abstract

The hyper-Erlang model can approximate any non-negative distribution as closely as desired. It can not only characterize field data well, but also facilitate analytically tractable results for performance evaluation. As a result, this model is widely used in telecommunication network modeling. This paper proposes an online algorithm for Gamma mixture distributions, which contain hyper-Erlang models as a special case, and applies the algorithm to Internet traffic modeling. Simulation and experimental results are also provided.