Modeling and Control for Next-Gerneration Integrated-Services Networks

研究人员建议通过非传统的建模和分析的方法来分析下一代网络的行为，研究下一代网络的控制和管理问题。在未来的综合业务网络中，拥塞现象的性质可能与互联网等更传统的系统中的拥塞现象截然不同。原因是，在单元级别，长期依赖和高度可变性的现象将在我们通过网络分析、设计和提供服务的方式中发挥重要作用。虽然这些现象已经在现有系统中观察到并进行了统计分析，但服务的集成预计会放大这些现象。这项拟议的研究的第一部分涉及对研究者最近的发现的进一步证明，这些发现解释了Levy过程是如何作为某些类型的远程依赖流量的宏观模型而产生的。论证是通过严格推导交通过程的概率分布的宏观近似来完成的。此外，还提出了与分数布朗运动的比较以及进一步的分析和模拟，并建议明确研究这些模型(特别是Levy过程)对性能和控制的影响。他建议使用样本路径公式和守恒定律来导出可解系统的显式解。具有稳定Levy运动输入的网络是显式可解的有希望的候选者。在续集中，为了处理不可解的情况，他建议研究分布和延迟的极端情况。这里涉及的任务要求将大偏差结果和应用扩展到具有反馈的网络。这项研究的影响将是理解拥堵在高度可变的环境中发生的方式，并将有助于防止网络中的灾难。所提出的控制方法涉及随机微分方程组，也可以解释为源于长程相关系统。通过研究最优控制问题，研究者提出了解决缓冲区管理方案。最后，他建议研究对随机交通施加确定性或塑造监管约束的影响，得出最坏情况的情景，并结合统计和确定性描述符。这项研究的影响将导致下一代网络描述符的进一步标准化。这些描述对于提供服务和设计正确的定价方案是无价的。这项拟议研究的一个相当重要的方面在于它的基本特征，即它重新审查了绩效模型，并选择了简单易处理的范例，这些范例可以传达给学生，也可以被行业使用。

The investigator proposes to analyze the behavior and study control and management issues for next generation networks by means of non-traditional modeling and analysis. In future integrated services networks, congestion phenomena are likely to be quite different in nature than those in more traditional systems such as the Internet. The reason is that, at the cell level, the phenomena of long-range dependence and high variability are going to play a major role in the way we analyze, design and provide services over a network. While these phenomena have already been observed and statistically analyzed in existing systems, integration of services is expected to amplify them. The first part of the proposed research deals witha further justification of the investigator's recent findings that explain how Levy processes arise asmacroscopic models of certain types of long-range dependent traffic. The justification is done by rigorously deriving macroscopic approximations of the probability distributions of the traffic processes. In addition, comparison with and further analysis and simulation of fractional Brownian motions is also proposed.The investigator also proposes to explicitly study the consequences of these models (and, in particular Levy processes) to performance and control. He proposes to use sample path formulas and conservation laws in order to derive explicit solutions of solvable systems. Networks in tandem with stable-Levy motions inputs are promising candidates for explicit solvability. In the sequel, and in order to deal with non-solvable situations, he proposes to examine extremes of distributions and delays. The tasks involved here call for extensions of large deviations results and applications to networks with feedback. The impact of this study will be the understanding of the way that congestions occur in highly variable environments and will,as in risk theory, help prevent catastrophes in networks. The proposed control methods involve stochasticdifferential equations that can also be explained as arising from long-range dependent systems. By studyingoptimal control problems, the investigator proposes to tackle buffer management schemes. Finally, he proposes to examine the impact of imposing deterministic or shaping regulatory constraints on stochastic traffic, derive worst-case scenaria and combine statistical and deterministic descriptors. The impact of this study will lead to further standardization of descriptors for next generation networks. Such descriptorsare invaluable for the provision of services and the design of correct pricing schemes. A rather significant aspect of the proposed research lies in its fundamental character in that it re-examines the performance models and opts for simple and tractable paradigms that can be communicated to students but also used by the industry.