RAPID: Improving Capabilities to Measure the Robustness of Critical Communications Infrastructure: A Case Study of COVID-19 Quarantine-Induced Internet Performance

RAPID：提高衡量关键通信基础设施稳健性的能力：COVID-19 隔离引起的互联网性能案例研究

• 批准号: 2028506
• 负责人: Ka Pui Mok
• 金额: $ 13.76万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-05-01 至 2020-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028506&HistoricalAwards=false
• 关键词: RAPID; Improving; Capabilities; Measure; Robustness

In the crisis of the CoVID-19 pandemic, the Internet is facing unprecedented surges of traffic induced by the use of cloud-based telecommuting and remote education tools for real-time video meetings and online classes. However, existing network throughput measurement (speed test) platforms are often not representative of the performance of cloud-based applications due to the location of test servers. Measuring the performance of interconnections between cloud platforms and Internet Service Providers (cloud-ISP links) is a critical missing piece to understanding user-experienced performance of cloud-based videoconferencing applications.This project will design and deploy novel experiments to measure network congestion of cloud-ISP links, tracking evolution of performance degradations during mandatory sheltering-in-place orders, and as large segments of the U.S. work force transition back to their workplaces. This scientific measurement project will tackle three challenges: 1) strategic selection of test servers within residential access and transit ISPs, based on topology measurements and analytics, 2) scientific characterization of the algorithms and behavior of speed tests, and 3) correct interpretation measurement results. The experiments will leverage speed test servers deployed by various commercial platforms (e.g., Ookla) as vantage points to conduct throughput measurements from cloud platforms hosting high-bandwidth applications. Operationalizing this experiment will provide longitudinal data to analyze performance degradation of cloud-ISP interconnections.This research will enable studying the performance and reliability of critical Internet infrastructures in the U.S. during this pandemic, by collecting and sharing data that sheds light on the quality of experience of cloud-based telework applications. Visualized data will be generated to provide longitudinal views of network performance, and identify performance degradations at fine granularity, geographically and topologically. The resulting tools and methods will help guide future infrastructure improvements, and advance the ability to monitor an increasing critical communications ecosystem.Detail information and the data of this project is available at https://webspeedtest.caida.org.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.

在新冠肺炎大流行的危机中，互联网正面临前所未有的流量激增，原因是基于云的远程办公和远程教育工具用于实时视频会议和在线课程。然而，由于测试服务器的位置，现有的网络吞吐量测量(速度测试)平台往往不能代表基于云的应用程序的性能。测量云平台和互联网服务提供商(云-isp链路)之间的互连性能是了解基于云的视频会议应用程序的用户体验性能的关键缺失部分。该项目将设计和部署新的实验来测量云-isp链路的网络拥塞，跟踪在强制就地庇护订单期间以及随着大部分美国劳动力返回工作场所时性能下降的演变。该科学测量项目将解决三个挑战：1)基于拓扑测量和分析，战略性地选择住宅接入和交通互联网服务提供商中的测试服务器；2)对速度测试的算法和行为进行科学表征；3)正确解释测量结果。这些实验将利用各种商业平台(如Ookla)部署的速度测试服务器作为有利条件，从托管高带宽应用的云平台进行吞吐量测量。将这项实验付诸实施将为分析云-互联网服务提供商互连的性能降级提供纵向数据。这项研究将通过收集和共享数据来研究美国关键互联网基础设施在此次大流行期间的性能和可靠性，这些数据有助于了解基于云的远程工作应用的体验质量。将生成可视化数据，以提供网络性能的纵向视图，并在细粒度、地理位置和拓扑结构上识别性能下降。由此产生的工具和方法将有助于指导未来的基础设施改进，并提高监控日益关键的通信生态系统的能力。该项目的详细信息和数据可在https://webspeedtest.caida.org.This奖励中获得，反映了国家科学基金会的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Measuring the network performance of Google cloud platform

测量Google云平台的网络性能

• DOI: 10.1145/3487552.3487862
• 发表时间: 2021
• 期刊: Proceedings of the 21st ACM Internet Measurement Conference
• 作者: Mok, Ricky K.;Zou, Hongyu;Yang, Rui;Koch, Tom;Katz-Bassett, Ethan;Claffy, K C
• 通讯作者: Claffy, K C