CAREER: New Traffic Models for Internet Connections and VBR video Traffic

互联网连接和VBR视频流量的新流量模型本项目研究互联网上应用和连接级流量的新模型。目的是更好地理解这种流量对网络拥塞的影响。互联网流量的非泊松统计性和远距离依赖性等特点是其与电路交换网络中典型流量的区别。当数据包通过网络从用户应用程序传输到目的地时，它会经历各种转换。这些线性和/或非线性的转换在随机的交通流中产生了结构特征。其结果是网络流量组合的高度可变性。识别和控制这些流量特征的来源在实时资源分配和网络流量工程中具有重要意义。本项目的工作使用测量的网络数据来确定建模Internet使用所需的特征空间。考虑了终端用户、网络协议和视频编码器产生的流量。非线性时间序列模型将用于表征连接和应用级流量。这些模型具有灵活性，可以处理从短期依赖随机过程到具有自相似和确定性特征的各种交通类型。在应用层面，重点研究了分层可变比特率视频的生成，以及编码参数对流量特性、模型参数和性能的影响。时间序列建模框架将用于设计具有感知和网络驱动成本约束的最优速率控制算法。所获得的流量模型将允许人们评估和控制终端系统，并为有问题的流量源提供网络级控制。研究结果还将提供定量评估，以确定哪种类型的流量可以产生合适的统计多路复用增益。与研究工作相结合，将开发网络性能领域的研究生和本科生课程。课程和项目将支持端到端解决问题的技能的发展。其目的是将工程和物理科学的研究和跨学科思想整合到电信相关问题的解决方案中。这个项目下正在进行的活动可在http://morse.uml.edu/-kchandra/career找到。

New Traffic Models for Internet Connections and VBR Video Traffic This project examines new models for application and connec- tion level traffic on the Internet. The objective is to better understand the impact of this traffic on network congestion. Features of Internet traffic such as its non- Poisson statistics and long range dependence are a point of departure from typical traffic on circuit switched networks. As packet traffic progresses from the user application to its destination across a network, it undergoes a variety of transformations. These linear and/or nonlinear transforma- tions give rise to structural features in an otherwise ran- dom traffic stream. The result is high variability in the network traffic mix. Identifying and controlling the source of these traffic features is important in real-time resource allocation and network traffic engineering. The work in this project uses measured network data to identify the feature space required to model Internet usage. Traffic generation from end users, network protocols and video-coders are con- sidered. Non-linear time-series models will be used to characterize connection and application level traffic. These models have the flexibility to address a range of traffic types from short-range dependent stochastic processes to those with self-similar and deterministic features. At the application level, particular attention is paid to the gen- eration of layered variable bit rate video and into the in- fluence of encoding parameters on traffic characteristics, model parameters and performance. The time-series modeling framework will be used to design optimal rate control algo- rithms with perceptual and network driven cost constraints. The traffic models obtained will allow one to assess and control end systems and provide network level control for problematic traffic sources. The results will also provide quantitative evaluation of what types of traffic can be su- perposed to yield suitable statistical multiplexing gains. In conjunction with the research effort, a graduate and un- dergraduate curriculum in the network performance area will be developed. The courses and projects will support the development of end-to-end problem solving skills. The aim is to integrate research and interdisciplinary ideas from engineering and physical sciences into the solution of telecommunications related problems. Ongoing activities under this project can be found at http://morse.uml.edu/-kchandra/career.