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.

涉及带宽的应用程序（例如视频流的流行）以及资源受限的移动网络的普及，重新激发了有关如何由Internet服务提供商（ISP）对待网络流量如何处理的讨论。为了管理稀缺的网络资源，ISP使用Middleboxs选择性执行网络策略（例如，视频流的限制传输速率）。这项研究将探讨中间箱对网络流量的影响，以及领导网络用户，政策制定者和监管机构对在运营网络中部署的政策进行更深入的了解。该项目解决了三个关键挑战，这些挑战限制了研究人员对米德箱强加的网络政策的理解。首先，研究人员努力表征政策，因为他们无法访问Middlebox进行实验。其次，研究人员缺乏模型的中间箱如何对网络流量进行分类和互动，因此很难对它们进行推理。最后，识别和理解中间箱行为通常需要从网络内部的有利位置进行测量。这项调查需要在商业米中盒上进行黑盒和灰色盒实验，以构建其操作方式的准确模型，并使用这些观察值来构建可扩展，灵活和现实的测试台，以评估检测和隔离网络策略的方法。该项目将结合基于痕量的分析，以设计有效的弹性算法，以从最终系统中检测这些属性，并进行优化以使该检测系统量表。为了概括我们的结果，PI将发展一个理论，说明中间箱如何影响流量，如何从端点检测这些中间箱，可能在网络上可见性的情况下。