An improved fast algorithm for simulating self-similar traffic with application in ATM networks

This paper presents an improved self-similar traffic generator, based on fast fractional Gaussian noise, for the purpose of fast simulation of long term correlation of self-similar traffic. The algorithm developed in this study is more efficient than existing methods since it only requires Hurst parameter and can arrive higher accurate sample points if necessary. The effectiveness of these methods has been demonstrated by some numerical examples.