Collaborative Research: A Control Theoretic Approach to the Design of Internet Traffic Managers

互联网的可扩展性取决于我们驯服与其开放架构相关的不可预测性的能力。本项目研究减少流量突发和提高网络利用率的基本控制策略的发展。这样的策略可以通过流量管理器(TM)来应用，流量管理器(TM)是战略性地放置在互联网中的特殊网络元素(例如，在客户端/服务器之前或在管理域之间的交换/对等点处)。我们认为，这种控制功能的结合将是网络基础设施保持自身增长和满足新兴应用的服务质量(Qos)需求的关键。尽管最近在构建能够进行线速处理的网元方面取得了一些进展，但有必要对这些TM应该实施的基本QOS控制能力进行基础研究。必须在可编程、可伸缩的体系结构中标识和实现这组功能，以便轻松有效地组合服务。随着互联网的不断发展和用户对其应用程序的新类型服务的需求，这种灵活的体系结构是非常理想的。TMS应该能够在数据包经过时对其进行快速检测和分类(例如，将数据包标记为优先级)，并且应该控制这些数据包的传输(例如，通过定步、调度或选择性丢弃)，以确保期望的特性(例如，满足抖动要求、符合TCP友好性或改善流之间的公平性)。在该方案中，我们将讨论动态DoS控制程序的设计。我们专注于可以在控制体系结构的不同级别上使用的基本功能。这些功能包括差异化控制、聚合控制和代理控制。下面是TM如何使用这种控制策略的示例。区分控制使TMS能够在不同的通信路径上路由具有不同特征的流聚合。与传统路由不同，我们的路由度量将尊重自相似性和流量相关性等Bursitis度量：Aggregate Control使TMS能够对共享相同瓶颈的流集合使用拥塞控制机制。与传统的拥塞控制不同，“拥塞等价”流是基于关系度量(如互相关和互协方差)识别的，并作为一个集合进行管理；代理控制使TMS能够在更短的时间尺度上过滤掉可变性(例如，丢失、延迟抖动)。这种功能对于提高在较长时间尺度上(例如，端到端)运行的控制机制的稳定性和有效性至关重要。与传统的自组织代理方法不同，我们的方法将考虑在TM和终端系统之间形成的控制环路的长度和特征。我们的设计将基于控制理论和小波分析的数学基础。这些方法能够在不同的时间尺度上对系统动力学进行透彻的分析和控制，并理解它们之间的复杂相互作用。具体地说，TM架构不同级别的功能将基于集成的控制理论模型进行开发。这些模型将考虑由系统特性驱动的“嵌套”控制回路，这些特性使用被动测量的小波分析来识别。以这种集成方式设计的TM可以增加流量吞吐量，减少流量抖动和响应时间，并提高网络的稳定性、利用率和可扩展性。我们计划在受控本地环境和互联网上部署测试部署的DoS控制。我们的实施将基于DiffServ和MPLS等新兴技术，并将重点放在对带宽和服务质量要求高的应用上。我们的试验台将为软服务提供编程接口，其中功能可以打开或关闭，控制参数可以动态调整。为此，我们获得了工业研究实验室和初创公司的支持，这些公司包括朗讯的贝尔实验室、思科系统、北电网络和Quarry Technologies。具体地说，我们打算将朗讯的网元用于可编程数据包注入(NEPPI)。NEPPI提供了一个理想的基础，在此基础上实施我们建议制定的控制政策。该项目是波士顿大学(Ibrahim Matta、Azer Bestavros和Mark Crovella)和亚利桑那大学(PI：Marwan Krunz)合作完成的，前者擅长互联网流量的表征、测量和控制，后者擅长流量建模、多媒体和无线服务质量。

The scalability of the Internet hinges on our ability to tame the unpredictability associated with its open architecture. This project investigates the development of basic control strategies for reducing traffic burstiness and improving network utilization. Such strategies can be applied through Traffic Managers (TMs)-special network elements strategically placed in the Internet (e.g., in front of clients/servers or at exchange/peering points between administrative domains). We believe that the incorporation of such control functionalities will be key to the ability of the network infrastructure to sustain its own growth and to nurture the Quality-of-Service (QoS) needs of emerging applications.Although there have been some recent advances in building network elements capable of wire-speed processing, there is a need for fundamental research into the basic QoS control capabilities that these TMs should implement. This set of capabilities have to be identified and implemented in a programmable, scalable architecture that allows for the easy and effective composition of services. Such a flexible architecture is highly desirable as the Internet continues to evolve and users demand new kinds of service for their applications. TMs should be capable of quickly inspecting and classifying packets as they go by (e.g., marking packets into precedence classes), and should control the transmission of these packets (e.g., through pacing, scheduling, or selective dropping) to ensure desirable properties (e.g., satisfaction of jitter requirements, compliance with TCP friendliness, or improved fairness across flows).In this proposal, we will address the design of dynamic dos control programmable TMs. We focus on basic capabilities that could be employed at different levels of the control architecture. These capabilities include differentiated, aggregate and proxy controls. The following are examples of how such control strategies would be employed by TMs.Differentiated Control enables TMs to route flow aggregates with divergent characteristics on separate communication paths. Unlike traditional routing, our routing metrics will respect bursitis measures, such as self-similarity and traffic correlation:Aggregate Control enables TMs to use congestion control mechanisms for collections of flows that share the same bottleneck. Unlike traditional congestion control, "Congestion-equivalent" flows are identified based on measures of relationship (such as cross-correlation and cross-covariance) and managed as a set; Proxy Control enables TMs to filter out variability (e.g., loss, delay jitter) at shorter time-scales. Such a functionality is crucial for improving the stability and effectiveness of control mechanisms that operate over longer time-scales (e.g., end-to-end). Unlike traditional a-hoc proxy approaches, our approach will take into account the length and characteristics of the control loops that get formed between the TM and the end-systems.Our design will be based on mathematical foundations from control theory and wavelet analysis. These methods enable thorough analysis and control of system dynamics at different time-scales and an understanding of the complex interactions among them. Specifically, functionality's at different levels of a TM architecture will be developed based integrated control-theoretic models. These models will account for "nested" control loops that are driven by system characteristics, which are identified using wavelet analysis of passive measurements. TMs that are designed in such and integrated fashion, could increase flow throughput, reduce flow jitter and response time, and improve the stability, utilization, and scalability of the network.We plan to implement our dos controls in a tested deployed in a controlled local setting as well as over the Internet. Our implementations will be based on emerging technologies, such as Diffserv and MPLS, and will be stressed by bandwidth-and QoS-demanding applications. Our testbed will provide a programming interface to softservices, in which capabilities can be turned on or off and control parameters can be dynamically adjusted. To this end, we have secured the support of industrial research laboratories and start-up companies-namely Lucent's Bell Labs, Cisco Systems, Nortel Networks, and Quarry Technologies. Specifically, we intend to use Lucent's Network Element for Programmable Packet Injection (NEPPI). NEPPI provides an ideal foundation upon which to implement the control policies we propose to develop. This project is a collaborative efforts between Boston University (Is: Ibrahim Matta, Azer Bestavros, and Mark Crovella) with expertize in characterization, measurements and control of Internet traffic, and University of Arizona (PI: Marwan Krunz) with expertize in traffic modeling, multimedia and wireless QoS.