Comparison of the independent wavelet models to network traffic

In our previous work, we showed empirically that independent (Haar) wavelet models were parsimonious, computationally efficient and accurate in modeling heterogeneous network traffic measured by both autocovariance functions and buffer loss rate. We also proved analytically that such models were capable of capturing any decay rate of auto-covariance functions at large lags. In this work, we focus on comparing independent (Haar) wavelet models against independent wavelet models with higher vanishing moments. It is shown that as the vanishing moments increase, the independent wavelet model have better performance in approximating auto-covariance function at small lags. The computational cost for all independent wavelet model is O(N) for a trace of length N .