ITR: Optimal Diffusion Mechanisms for Fast and Robust TCP Congestion Control

ITR：快速、鲁棒 TCP 拥塞控制的最佳扩散机制

• 批准号: 0312851
• 负责人: Gonzalo Arce
• 金额: $ 35万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0312851&HistoricalAwards=false
• 关键词: ITR; Optimal; Diffusion; Mechanisms; Fast

Random Early Detection (RED), introduced in the early 90's emerged as the first significant Active Queue Management (AQM) designed to coexist with TCP - a concept that revolutionized congestion control of the Internet. Although numerous improvements on RED have been proposed recently, such as Adaptive RED, SRED, REM, and BLUE, many of the fundamental weaknesses inherent in all of these AQM protocols have not been overcome, including over-parameterization, design and implementation complexity, and the lack of robustness to varying traffic mixtures. The proposed research focuses on developing a new generation of active congestion control mechanisms based on the concept of optimal error diffusion discovered in signal processing and extensively used today in this field. Notably a duality exists between the mechanisms in packet marking or dropping with that of optimal dithering and quantization in signal processing. More precisely, (binary) quantization is analogous to packet marking where the average queue length, used as the input to RED, is quantized to "on" (marking) or "off" (no marking). The quantization (marking) error is then diffused over to subsequent quantization (marking) operations. Optimal quantization or dithering is attained with the so-called error diffusion filter, which, when applied to the AQM problem leads to remarkably efficient congestion control mechanisms coined here as Diffusion Early Marking (DEM). Unlike many AQM systems, random variable generation is not required as error diffusion attains optimal (pseudo-random) dithering, and more importantly DEM only requires a single control parameter which is designed based on the estimation of active flows or on other network statistics measuring congestion. As such, the proposed methods rely on cross level interactions for improved AQM performance. Expectation maximization (EM) algorithms and other simpler statistical methods applied on ECN markings, for instance, promise to provide adequate and robust estimates of congestion. The mechanisms in DEM thus allow it to maintain a stable average queue length with a varying number of flows. Preliminary results on the design and optimization of DEM are remarkably promising. There are however, numerous open problems that need to be addressed prior to its implementation including: (a) methods for the optimal design of parameters controlling rate and queue-length based packet drop mechanisms, (b) fast and robust estimation of the number of active flows and network congestion based on packet header information and/or queue dynamics, (c) diffusion mechanisms for networks with mixed traffic including web mice and elephants, (d) development of DEM differentiated service mechanisms. The major contribution of the proposed research is on the application of the rich theories of quantization and robust estimation to the design of novel and robust AQM mechanisms that rely on cross-layer information. The new AQM mechanisms, in concert with the estimation framework to be developed, promise to adequately control the congestion of networks with various traffic mixtures and non-stationary traffic dynamics. An important aspect of the proposed work is the testing of DEM routers with real traffic in an experimental and scalable testbed. The availability of this testbed will be valuable in providing students with a deeper understanding of difficult network concepts, such as congestion control and active queue management, and allowing then to gain hands-on experience in network traffic management and control.

随机早期检测（RED）于90年代初推出，是第一个重要的主动队列管理（AQM），旨在与TCP共存--这一概念彻底改变了互联网的拥塞控制。虽然最近已经提出了许多改进的RED，如自适应RED，SRED，REM，和蓝色，许多根本的弱点，在所有这些AQM协议中固有的尚未克服，包括过度参数化，设计和实现的复杂性，并缺乏鲁棒性变化的流量混合。建议的研究重点是开发新一代的主动拥塞控制机制的基础上发现的信号处理和广泛使用的今天在这个领域的最佳误差扩散的概念。值得注意的是，在分组标记或丢弃机制与信号处理中的最佳抖动和量化机制之间存在对偶性。更确切地说，（二进制）量化类似于分组标记，其中用作RED的输入的平均队列长度被量化为“开”（标记）或“关”（无标记）。量化（标记）误差然后被扩散到随后的量化（标记）操作。最佳量化或抖动达到所谓的误差扩散过滤器，其中，当应用到AQM问题导致非常有效的拥塞控制机制，在这里创造的扩散早期标记（DEM）。与许多AQM系统不同，不需要随机变量生成，因为误差扩散达到最佳（伪随机）抖动，更重要的是，DEM只需要一个单一的控制参数，该参数是基于对活动流的估计或其他网络统计测量拥塞而设计的。因此，所提出的方法依赖于跨级别的相互作用，以提高AQM性能。例如，应用于ECN标记的期望最大化（EM）算法和其他更简单的统计方法有望提供充分和可靠的拥塞估计。因此，DEM中的机制允许它在不同数量的流的情况下保持稳定的平均队列长度。DEM的设计和优化的初步结果是非常有前途的。然而，在实施之前，仍有许多悬而未决的问题需要解决，其中包括：（a）用于控制基于速率和队列长度的分组丢弃机制的参数的最优设计的方法，（B）基于分组报头信息和/或队列动态对活动流的数量和网络拥塞的快速和鲁棒估计，（c）混合流量网络的扩散机制，包括网络鼠标和大象，（d）DEM差异化服务机制的发展。所提出的研究的主要贡献是丰富的量化和鲁棒估计理论的应用，设计新颖的和强大的AQM机制，依赖于跨层信息。新的主动队列管理机制，与估计框架的发展，承诺充分控制网络的拥塞与各种交通的混合和非平稳的交通动态。所提出的工作的一个重要方面是测试DEM路由器与真实的流量在实验和可扩展的测试床。该测试平台的可用性将有助于学生更深入地了解复杂的网络概念，如拥塞控制和主动队列管理，并使他们能够获得网络流量管理和控制方面的实践经验。