Heterogeneous Network Traffic Modeling and Analysis in Wavelet Domain

随着多媒体流量开始主导宽带网络，视频和数据流量的精确建模对于许多重要的网络应用变得至关重要。视频和数据流量最近被发现具有复杂的自相似性，使以前开发的流量无效 模型其中最重要的问题之一是如何开发计算效率高，但准确的模型，可以捕捉复杂的统计特性的视频和数据流量的网络设计/控制。 本研究的目标是开发一个统一的模型，它是（1）能够模拟异构多媒体流量，包括VBR视频和数据，（2）计算效率高，（3）可行的分析。 为了实现我们的目标，我们建议使用小波。我们将表明，虽然异构多媒体业务具有复杂的短期和长期的时间依赖性，相应的小波系数不再是长期依赖。因此，可以使用简单的方法来建模 小波域中的网络流量。特别地，独立小波 模型已被证明是足够准确，吝啬， 具有可达到的最低计算复杂度。 我们将集中精力研究如何使用独立的 小波分析模型，包括自相关，缓冲区丢失率。我们还将研究如何将小波模型应用于网络控制，如接纳控制。

As multi-media traffic begins to dominate broadband networks, accurate modeling of video and data traffic becomes crucial to many important network applications. Video and data traffic has recently been found to possess complicated self-similarity that invalidates previously developed traffic models. One of the most important problem is how to develop computationally efficient and yet accurate models which could capture the complicated statistical properties of video and data traffic for network design/control. Our objective of this research is to develop a unified model which is (1) able to model heterogeneous multi-media traffic including VBR video and data, (2) computationally efficient, and (3) feasible for analysis. To accomplish our goal, we propose to use wavelets. We will show that although heterogeneous multi-media traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no-longer long-range dependent. Therefore, simple methods can be used to model network traffic in the wavelet domain. In particular, independent wavelet models have shown to be sufficiently accurate, parsimonious, and have the lowest computational complexity attainable. We will focus our efforts on investigating how to use independent wavelet models for analysis including anto-correlation, and buffer loss rate. We will also investigate how to apply wavelet models to network control such as admission control.