NeTS: Small: A Principled Approach to Enabling Policy Transparency for Mobile Networks

NetS：小型：实现移动网络政策透明度的原则性方法

• 批准号: 1617728
• 负责人: David Choffnes
• 金额: $ 29.96万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1617728&HistoricalAwards=false
• 关键词: NeTS; Small; Principled; Approach; Enabling

The rise in popularity of bandwidth-hungry applications such as video streaming, and the popularity of resource-constrained mobile networks has reignited discussions about how network traffic associated with different applications is treated by Internet Service Providers (ISPs). To manage scarce network resources, ISPs use middleboxes to selectively enforce network policies (e.g., limit transfer rates for video streaming). This study will explore the impact of middleboxes on network traffic, and lead network users, policymakers, and regulators to a deeper understanding of policies deployed in operational networks.This project addresses three key challenges that limit researchers' understanding of network policies imposed by middleboxes. First, researchers struggle to characterize policies because they have limited or no access to middleboxes for experimentation. Second, researchers lack models of how middleboxes classify and interact with network traffic, making it difficult to reason about them. Finally, identifying and understanding middlebox behavior often requires measurements from vantage points inside the network. This investigation entails black-box and grey-box experiments on commercial middleboxes to build accurate models of how they operate, and using these observations to build a scalable, flexible and realistic testbed for evaluating methods to detect and isolate network policies. This project will incorporate trace-based analysis to design efficient, resilient algorithms to detect these properties from end systems, and optimizations to make this detection system scale. To generalize our results, the PIs will develop a theory of how middleboxes can impact traffic, how to detect these middleboxes from endpoints, potentially with limited visibility into the network.

视频流等高带宽应用程序的普及以及资源有限的移动网络的普及重新引发了有关互联网服务提供商 (ISP) 如何处理与不同应用程序相关的网络流量的讨论。为了管理稀缺的网络资源，ISP 使用中间盒有选择地实施网络策略（例如，限制视频流的传输速率）。本研究将探讨中间盒对网络流量的影响，并引导网络用户、政策制定者和监管机构更深入地了解运营网络中部署的策略。该项目解决了限制研究人员理解中间盒所施加的网络策略的三个关键挑战。首先，研究人员很难描述政策的特征，因为他们有限或无法使用中间件进行实验。其次，研究人员缺乏中间件如何对网络流量进行分类和交互的模型，因此很难对其进行推理。最后，识别和理解中间件行为通常需要从网络内部的有利位置进行测量。这项调查需要对商业中间盒进行黑盒和灰盒实验，以构建其运行方式的准确模型，并利用这些观察结果构建一个可扩展、灵活且现实的测试平台，用于评估检测和隔离网络策略的方法。该项目将结合基于跟踪的分析来设计高效、有弹性的算法来检测终端系统的这些属性，并进行优化以使该检测系统具有规模。为了概括我们的结果，PI 将开发一种关于中间盒如何影响流量、如何从端点检测这些中间盒（可能对网络的可见性有限）的理论。