CNS Core: Small: Collaborative Research: Improving the Reliability of Cable Broadband Networks with Proactive Network Maintenance

CNS 核心：小型：协作研究：通过主动网络维护提高有线宽带网络的可靠性

• 批准号: 1910867
• 负责人: Xiaowei Yang
• 金额: $ 34.72万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910867&HistoricalAwards=false
• 关键词: CNS; Core; Small; Collaborative; Research

High-speed Internet access plays an important role in modern life. It helps narrow the digital divide, enables e-commerce, and provides opportunities for remote work, study, and entertainment. In the US, cable Internet Service Providers (ISPs) are one of the few available infrastructures that can provide high-speed Internet access to US homes, and in many rural areas, they are often the only broadband choice. However, much measurement study has shown that broadband access networks have poor reliability. (Many parts of the cable networks are now decades old.) This work aims to address this problem. If successful, it can significantly improve the reliability of cable broadband networks, thereby improving Internet availability and quality of experience of millions of cable broadband users.It is challenging to improve the reliability of cable networks because the "last-mile" links that connect a subscriber's home to the Internet are often made of coaxial cables. They are vulnerable to radio frequency interference and suffer from aging-related issues. These problems can manifest themselves as unrecoverable noisy signals, disrupting a subscriber's Internet connectivity. The cable industry currently collects performance data from users' cable modems. However, there is a lack of systematic study on how to use this data to detect and localize network problems and to rank the severity of problems. Existing techniques often lead to an unacceptably high number of false positives in practice. This work will develop algorithms and tools that can help detect and localize faults in cable networks and estimate the performance impact of network faults. Specifically, the work will include 1) algorithms that use collected data to accurately detect faults inside a cable network; 2) algorithms that localize a fault to a geographical location by clustering anomalous data patterns; and 3) algorithms that estimate how many calls an ISP may receive given a network problem as a mechanism to prioritize repairs. In this project, these algorithms will be implemented in software. All algorithms and code resulting from this work will be made publicly available. The researchers anticipate that the algorithms developed in this project are also applicable to WiFi and cellular networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

高速互联网访问在现代生活中起着重要作用。它有助于缩小数字鸿沟，启用电子商务，并为远程工作，学习和娱乐提供机会。在美国，有线互联网服务提供商（ISP）是可以为美国家庭提供高速互联网访问的少数可用基础架构之一，在许多农村地区，它们通常是唯一的宽带选择。但是，许多测量研究表明，宽带访问网络的可靠性差。 （电缆网络的许多部分现在已经有几十年了。）这项工作旨在解决此问题。 如果成功的话，它可以显着提高电缆宽带网络的可靠性，从而提高互联网的可用性和数百万有线宽带用户的经验质量。它具有挑战性地提高有线电视网络的可靠性，因为将订户与互联网连接到Internet的“最后一英里”链接通常是由同轴电缆组成的。它们容易受到无线电频率干扰的影响，并且遭受与衰老有关的问题。这些问题可以表现为无法恢复的嘈杂信号，从而破坏了订户的Internet连接性。 电缆行业目前从用户的电缆调制解调器中收集性能数据。但是，缺乏关于如何使用此数据来检测和本地化网络问题并对问题严重性进行排序的系统研究。现有技术通常会导致实际上误报数量不高。 这项工作将开发算法和工具，可以帮助检测和本地化有线网络中的故障并估算网络故障的性能影响。 具体而言，工作将包括1）使用收集的数据准确检测有线网络中的故障的算法； 2）通过聚集异常数据模式将故障定位到地理位置的算法； 3）估计ISP可能会接收到网络问题的算法，以作为确定维修优先级的机制。在此项目中，这些算法将在软件中实现。这项工作产生的所有算法和代码都将公开可用。研究人员预计，该项目中开发的算法也适用于WiFi和蜂窝网络。该奖项反映了NSF的法定任务，并且使用基金会的智力优点和更广泛的审查标准，被认为值得通过评估来获得支持。

项目成果

CableMon: Improving the Reliability of Cable Broadband Networks via Proactive Network Maintenance

• 发表时间: 2020
• 作者: Jiyao Hu;Zhenyu Zhou;Xiaowei Yang;Jacob Malone;Jonathan W. Williams

Characterizing Physical-Layer Transmission Errors in Cable Broadband Networks

表征有线宽带网络中的物理层传输错误

• 发表时间: 2022
• 期刊: 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI ’22
• 作者: Hu, Jiyao;Zhou, Zhenyu;Yang, Xiaowei
• 通讯作者: Yang, Xiaowei