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

Internet连接和VBR视频流量的新流量模型 该项目研究了应用和连接的新模型， 互联网上的流量。目标是 更好地了解此流量对网络的影响 拥堵 互联网流量的特点，如它的非泊松统计和长程相关性是一个点， 与电路交换网络上的典型业务量不同。 随着数据包流量从用户应用程序进展到 它的目的地在网络上，它经历了各种各样的 转变 这些线性和/或非线性变换 在其他情况下会产生结构特征- DOM流量流。结果是， 网络流量混合。 识别和控制源头 这些流量特征在实时资源中是重要的 分配和网络流量工程。这项工作 项目使用测量的网络数据来识别要素 为Internet使用建模所需的空间。流量生成 从最终用户，网络协议和视频编码器是con- 侧着身子。 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，可以处理各种流量 从短期依赖随机过程到 具有自相似性和确定性特征的那些。在 应用层面，特别注意的是， 分层的可变比特率视频的操作，并进入该信息中， 编码参数对业务特性的影响， 模型参数和性能。时间序列建模 框架将用于设计最优速率控制算法， 具有感知和网络驱动成本约束的算法。 获得的交通模型将使人们能够评估并 控制终端系统，并提供网络级控制， 交通来源问题。结果还将提供 定量评估什么类型的交通可以被苏， 用于产生适当的统计复用增益。 在研究工作的同时，一个研究生和联合国- 网络性能领域研究生课程 将被开发。课程和项目将支持 开发端到端解决问题的技能。目的 是整合研究和跨学科的想法， 工程和物理科学的解决方案， 电信相关问题。 该项目下正在开展的活动见： http://morse.uml.edu/-kchandra/career.

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.