CAREER: Exploiting Tomography in Network-Aware Protocols: Theory and Practice

我们研究的总体目标是解决可扩展和网络自适应的覆盖网络问题，包括负载均衡、优化的分散路由和低开销网络监控。为了实现这一目标，我们将设计新颖的技术，在空间和时间上利用端到端测量进行推理和在线适应。我们的技术将在包括三个组件的系统中实现和评估：1.用于组播、任播、地理广播和对等服务的覆盖网络：我们将设计方法来推断潜在的网络特征(例如，拓扑、损耗)和主机属性(例如，位置、剩余电池电量)，并利用它们来适应互联网上的覆盖树和网格。我们还将对各种覆盖网络类别的结构、动态和性能进行建模和表征。了解和隔离Internet拓扑和覆盖构建算法的影响将是这项工作的重要组成部分。负载均衡、优化的分散路由和协调的拥塞控制：我们将研究利用延迟/丢失测量之间的相关性来根据推断的瓶颈实时划分TCP或应用层流的可行性。生成的流分区可用于持续平衡负载，利用分散的路由和并行路径，并做出协调的拥塞避免决策。3.分布式网络监控：我们将设计基于轻量级断层扫描的方法来持续诊断网络问题，并根据推断的网络特征检测异常或攻击。基于我们的解决方案和相关研究(1)网络层和应用层交互；(2)覆盖特性、成本和动态；以及(3)在线断层扫描的可行性，我们将准备将我们的范围从覆盖网络扩展到网络安全、无线和传感器网络中的其他挑战性问题。拟议的研究涵盖了网络的各个方面(从理论到实现)，并将为研究生提供平衡的理论和实践，这对他们未来的职业生涯将是非常有价值的。此外，这项研究将与实验室和研讨会的发展以及从高中到研究生的指导和推广活动相结合。这些项目旨在通过吸引学生参与高质量的网络研究，来增加“女性”学生的参与度和留校率。将开发一套基于网络的图形用户界面和实验作业，用于网络模拟和测量，利用我们建议的研究软件以及研究实验室和大学提供的工具。这些实验室将帮助高中生和本科生在一个有趣的环境中欣赏互联网的规模、异质性和动态性。本科生和研究生导师，以及有行业参与的研究研讨会，将鼓励学生，特别是女性，从事博士水平的研究。所有的实验和研讨会材料都将在网上免费提供，以供其他机构的类似项目使用。

The overarching goal of our research is to address the problem of scalable and network-adaptive overlay networking, including load balancing, optimized dispersity routing, and low-overhead network monitoring. To achieve this goal, we will design novel techniques for spatially and temporally exploiting end-to-end measurements for inference and on-line adaptation. Our techniques will be implemented and evaluated in a system that includes three components:1. Overlay networks for multicast, anycast, geocast, and peer-to-peer services: We will design methods to infer underlying network characteristics (e.g., topology, losses) and host properties (e.g., location, remaining battery power), and exploit them for adapting overlay trees and meshes on the Internet. We will also model and characterize the structure, dynamics, and performance of various overlay network classes. Understanding and isolating the impacts of Internet topology and the overlay construction algorithm will be an integral component of this work.2. Load balancing, optimized dispersity routing, and coordinated congestion control: We will study the feasibility of using correlations among delay/loss measurements to partition TCP or application-layer flows according to inferred bottlenecks in real time. The resultant flow partitions can be used to continuously balance loads, utilize dispersity routing and parallel paths, and make coordinated congestion avoidance decisions. 3. Distributed network monitoring: We will design lightweight tomography-based methods to continuously diagnose network problems and detect anomalies or attacks based on inferred network characteristics. Based on our solutions and the associated studies of (1) network-layer and application-layer interactions; (2) overlay properties, cost, and dynamics; and (3) the feasibility of on-line tomography, we will be poised to expand our scope from overlay networks, to other challenging problems in network security, and wireless and sensor networks.The proposed research covers various facets of networking (from theory to implementation) and will provide graduate students with a balanced exposure to both theory and practice that will be invaluable in their future careers. In addition, the research will be integrated with lab and seminar development and mentoring and outreach activities that span levels from high school to graduate students. The programs aim at increasing *women* student participation and retention statistics, by attracting students to quality networking research. A set of web-based graphical user interfaces and lab assignments for network simulation and measurement will be developed, leveraging both our proposed research software, and tools available from research labs and universities. These labs will aid high school and undergraduate students appreciate the scale, heterogeneity and dynamics of the Internet in an interesting environment. Undergraduate and graduate mentoring, and research seminars with industry involvement, will encourage students, especially women, to pursue research to the PhD level. All labs and seminar material will be made freely available on the Web for the benefit of similar programs at other institutions.