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

随机早期检测(RED)在90年代初引入，S作为第一个重要的主动队列管理(AQM)出现，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对RED的改进，例如自适应RED、SRED、REM和BLUE，但这些AQM协议中固有的许多基本弱点还没有被克服，包括过度参数化、设计和实现复杂性以及对不同的业务混合缺乏健壮性。提出的研究重点是基于信号处理中发现的最优误差扩散的概念来开发新一代主动拥塞控制机制，目前在该领域得到了广泛的应用。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二元性。更准确地说，(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“ON”(标记)或“OFF”(无标记)。量化(标记)误差然后被扩散到随后的量化(标记)操作。最优量化或抖动是通过所谓的误差扩散滤波来实现的，当应用于AQM问题时，它导致了非常有效的拥塞控制机制，在这里被称为扩散早期标记(DEM)。与许多AQM系统不同的是，由于误差扩散获得最佳(伪随机)抖动，因此不需要随机变量生成，更重要的是，DEM只需要单个控制参数，该参数是基于对活动流的估计或其他测量拥塞的网络统计来设计的。因此，所提出的方法依赖于跨层交互来改进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承诺提供足够和稳健的拥塞估计。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。在数字高程模型设计和优化方面取得的初步成果是非常有希望的。然而，在其实施之前需要解决许多未解决的问题，包括：(A)用于控制速率和基于队列长度的分组丢弃机制的参数的优化设计的方法；(B)基于分组报头信息和/或队列动态对活动流和网络拥塞的快速和稳健的估计；(C)用于具有包括网络鼠标和大象的混合业务的网络的扩散机制；(D)DEM区分服务机制的发展。该研究的主要贡献在于将丰富的量化和稳健估计理论应用于设计依赖于跨层信息的新颖且稳健的AQM机制。新的AQM机制与即将开发的估计框架相结合，有望充分控制具有各种交通混合和非平稳交通动态的网络的拥塞。提出的工作的一个重要方面是在实验和可扩展的试验台上测试具有真实流量的DEM路由器。此试验台的提供将有助于学生更深入地了解拥塞控制和主动队列管理等复杂网络概念，并获得网络流量管理和控制的实践经验。

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.