Statistical Multiplexing of Self-similar Traffic

The network performance is influenced by the self-similarity of traffic, which is characterized by Hurst parameter. Self-similarity of multiplexing traffic as FBM (fractal brownian model) is investigated. Because the multiplexing self-similar traffic is asymptotic self-similar in nature, wavelet-based simulation demonstrates that the conventional multiplexing theory is conservative as not to utilize the network resources fully. Furthermore, within the FBM, most of self-similarity is contributed by the large variance traffic. This can be used to develop an effective method to diminish the self-similarity.