Modeling Heterogeneous Network Tra c in Wavelet Domain : Part II { Non - Gaussian Tra c

Following our work described in Part I of this paper that modeled various correlation structures of Gaussian traac in wavelet domain, we extend our previous models to heterogeneous network traac with either a non-Gaussian distribution or a periodic structure. To include a non-Gaussian distribution, we rst investigate what higher-order statistics are pertinent by exploring a relationship between timescale analysis of wavelets and cumulative traac. We then develop a novel algorithm in the wavelet domain to capture the important statistics. By utilizing local properties of wavelet basis in both space and time, we further extend such wavelet models to periodic MPEG traac. As wavelets provide a natural t to higher-order statistics as well as localized spatial and temporal dependence of periodic traac at diierent time scales, the resulting wavelet models for both non-Gaussian and periodic traac are simple and accurate with the lowest computational complexity attainable.