PECASE: Modeling, Analysis and Control of Subexponential Traffic Streams in Multimedia Networks

越来越多的经验证据表明，在现代多媒体网络中，业务流具有次指数、重尾、长相关和自相似的统计特性。具有次指数特性的业务流的示例范围从可变比特率(VBNS)压缩视频到各种Web和互联网相关应用。具有这些特征的业务流从根本上不同于传统的语音流。这种差异不仅是数量上的，而且是质量上的。例如，当在慢时间尺度上观察时，语音流量平均并且表现出非常小的波动，而vBNS视频流量在多个时间尺度上表现出动态统计行为；这通常被称为自相似行为。此外，与次指数随机序列的典型行为的较大偏差以与指数(例如语音)流完全不同的方式发生。在设计高效可靠的有线或无线多媒体通信网络时，了解这些新颖而有趣的统计现象是非常重要的。提高通信网络效率的最常见方法是通过共享网络资源，例如链路容量和缓冲空间。这一过程会导致个人网络用户感知的服务质量(Qos)的降低。设计目标是在一定的服务质量约束下最大化效率，例如时延分布和丢包率。这一设计过程自然分为以下三个方面：1)统计数据分析和流量建模；2)性能分析和控制；3)网络设计的数值和软件工具的构建。这三个研究领域内在地相互关联，任何一个领域的有效解决办法都必须以其他两个领域的进展为基础。因此，提出了一个全面和综合的研究议程，该建议的重点是对发展现有技术，如ATM、基于TCP/IP和无线数据网络以及可能适用于未来网络设计的基本问题进行研究。拟议的研究范围从概率论到软件工程。这种影响不仅限于多媒体通信网络，而且对于理解运筹学、金融和保险理论中的问题也很重要。在这些问题中，次指数模型扮演着重要的角色。除了拟议的研究外，还提出了一种将理论与计算相结合的课程。伟大的科学进步往往是通过理论和实验的相互作用而发生的。从这个角度来看，研究人员认为，工程师在职业生涯早期以统一的方式接触理论和实验知识是至关重要的。这使他们能够认识到理论和实验的潜力和局限性，并成功地将其用于自己的优势。这种方法还通过演示现实世界问题的理论结果来加快学习过程，并教会学生如何将实验观察中的基本信息抽象为永恒的设计原则。

Increasing empirical evidence has demonstrated the presence of subexponential, heavy-tailed, long range dependent and self-similar statistical characteristics of traffic streams in modern multimedia networks. Examples of traffic streams with subexponential characteristics range from variable bit rate (VBNS) compressed video to various Web and Internet related applications. Traffic streams with these characteristics differ radically from conventional voice streams. The difference is not only quantitative, but qualitative as well. For example, when observed on a slow time scale voice traffic averages out and shows very little fluctuations while VBNS video traffic exhibits a dynamic statistical behavior on multiple time scales; this is often termed self-similar behavior. Furthermore, large deviations from the typical behavior of a subexponential random sequence occur in a completely different manner than with an exponential (e.g., voice) stream. Understanding these novel and intriguing statistical phenomena is of utmost importance when designing efficient and reliable wired, or wireless, multimedia communication networks.The most common way of increasing the efficiency of communication networks is through the sharing of network resources, e.g., link capacity and buffer space. This process leads to the degradation of quality of service (QoS) that is perceived by individual network users. The design objective is to maximize the efficiency subject to the QoS constraints, e.g., delay distributions and loss probabilities. This design process naturally breaks down into the following three areas: 1) statistical data analysis and traffic modeling; 2) performance analysis and control; 3) construction of numerical and software tools for network design. These three areas of research are inherently interconnected and an effective solution used for any one of them must be based on the advances in the other two areas. Therefore, a comprehensive and integrated research agenda is suggested.The focus of this proposal is on fundamental problems that are important for developing current technologies, e.g., Atm., TCP/IP-based and wireless data networks, as well as being potentially applicable to future network designs. The scope of the proposed research ranges from probability theory to software engineering. The impact is not only limited to multimedia communication networks, but is also important for understanding the problems in operations research, finance and insurance theory where subexponential models play an important role.In addition to the proposed research, a curriculum that integrates theory with computing is presented. Great scientific advances have often occurred through an interplay of theory and experiment. From this perspective the researcher believes it is essential that engineers are exposed early in their careersto theoretical and experimental knowledge in a unified fashion. This enables them to recognize the potential and limitations of both theory and experimentation and use it successfully to their advantage. This approachalso speeds up the learning process by demonstrating theoretical results on real world problems and teaches students how to abstract the essential information from the experimental observations into ever-lasting design principles.