Collaborative Research: NeTS-NBD: A Revolutionary 4D Approach to Network-Wide Control and Management

IP网络是一个巨大的成功，促进了数据网络在全球学术机构、政府、企业和家庭之间的扩散。然而，尽管这种基础设施具有根本性的重要性，但今天的网络却令人惊讶地脆弱，并且越来越难以配置、控制和维护。使用一种全新的方法，研究团队将探索与网络控制和管理相关的一些基本问题。研究议程的重点是IP（第3层）网络，尽管主要研究人员（pi）打算创建同样适用于其他技术的网络原语和服务，如第2层网络（如以太网）。这项工作的出发点是指导网络控制的一组原则：网络范围的视图、网络级别的目标和直接控制。这些原则引导pi将网络功能重构为四个组件——数据、发现、传播和决策平面。通过这种架构（pi称之为网络控制和管理的4D方法），该团队打算创建、原型化和演示突破性机制，从而极大地简化和加强数据网络。智力影响：提出的研究将解决改善IP控制和管理的关键基本问题：如何从将决策逻辑与特定协议和机制混合的网络转向抽象和隔离决策逻辑并允许一系列有效实现的架构？如何从由许多不协调的、容易出错的机制组成的网络转变为由网络级目标以一致的方式驱动底层机制的网络？如何从人们设置参数（旋转旋钮），希望诱使系统达到理想状态的网络，发展到网络设计师可以直接表达控制，自动引导系统达到理想状态的网络？如何从人工管理员在决策支持系统中以缓慢的时间尺度利用网络范围视图和盒级功能的网络转变为网络本身实时利用这些信息的网络？更广泛的影响：拟议的研究旨在产生基础知识，将推动大规模网络体系结构、控制和管理方面的最新技术。它旨在为数据网络（在学术校园、数据中心、企业、城域、骨干）奠定基础，使其更健壮、更可发展，更不容易出现安全漏洞。工业伙伴参与这个项目将加速研究成果的转化。总的教育影响在于培养学生、博士后和研究人员，使他们能够跨越理论研究和系统研究之间的界限。它为学生提供了独特的机会，在对基本原理的深刻理解的指导下，从事系统工作，并创造性地利用他们的知识来构思和设计创新的软件工具和系统。研究小组将利用现有的机构项目，从早期阶段开始招募代表性不足群体的学生，并让他们参与研究项目。研究项目的结果将被整合到本科和研究生计算机科学课程中。所开发的软件工具将为参与院校研究生水平课程的课堂项目提供基础。pi将根据该项目的研究重点和目标创建研究生课程。研究结果也将被用作本科学习的案例研究，以增强学生对大型网络的主要建筑设计挑战和控制问题的理解

IP networking is a spectacular success, catalyzing the diffusion of data networking across academic institutions, governments, businesses, and homes, world-wide. Yet, despite the fundamental importance of this infrastructure, today's networks are surprisingly fragile and increasingly difficult to configure, control, and maintain. Using a clean-slate approach, the research team will explore a number of fundamental questions related to network control and management. The focus of the research agenda is on IP (layer-3) networks, though the principal investigators (PIs) intend to create networking primitives and services that apply equally well to other technologies, such as layer-2 networks (e.g., Ethernet networks). The starting point for the work is a small set of principles, guiding the control of the network: network-wide views, network-level objectives, and direct control. These principles lead the PIs to a refactoring of network functionality into four components---the data, discovery, dissemination, and decision planes. Via this architecture, which the PIs term the 4D approach to network control and management, the team intends to create, prototype, and demonstrate breakthrough mechanisms that will dramatically simplify and strengthen data networking.INTELLECTUAL IMPACT: The proposed research will address fundamental questions that are key to improving IP control and management: How to go from networks that blend decision logic with specific protocols and mechanisms to an architecture that abstracts and isolates the decision logic and admits a range of efficient implementations? How to go from networks that consist of numerous uncoordinated, error-prone mechanisms, to ones where the low-level mechanisms are driven in a consistent manner by network-level objectives? How to go from networks where people set parameters (twist knobs), hoping to coax the system to reach a desired state, to one where network designers can directly express controls that automatically steer the system toward the desired state? How to go from networks where human administrators leverage network-wide views and box-level capabilities at slow timescales in decision-support systems, to one where the network itself leverages this information in real time?BROADER IMPACT: The proposed research seeks to produce fundamental knowledge that will advance the state-of-the-art in large-scale network architecture, control and management. It intends to lay the groundwork for data networks (in academic campuses, data centers, enterprises, metro areas, backbones) that are more robust, more evolvable, and less prone to security breaches. The involvement of industrial partners in this project will accelerate the transfer of the research results into operation.The general educational impacts are in the training of students, postdocs and researchers, allowing them to cross boundaries between theoretical and system-oriented research. It offers students the unique opportunity to pursue systems work, guided by a deep understanding of fundamental principles, and to use their knowledge creatively to conceive and design innovative software tools and systems. The research team will use existing institutional programs to recruit and involve students from underrepresented groups into the research program from its earliest stages. The results of the research project will be integrated into the undergraduate and graduate computer science program. The software tools to be developed will provide the basis for class projects in the graduate-level courses of the participating institutions. The PIs will create graduate-level courses based on the project's research priorities and goals. The findings will also be used as case studies in undergraduate studies to enhance students' understanding of the main architectural design challenges and control issues of large-scale networks