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COVID-19大流行的危机中，互联网面临着使用基于云的远程办公和远程教育工具在实时视频会议和在线课程中引起的前所未有的交通浪潮。但是，由于测试服务器的位置，现有的网络吞吐量测量（速度测试）平台通常不能代表基于云的应用程序的性能。衡量云平台和互联网服务提供商（云ISP链接）之间互连的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。本项目将设计和部署新型实验，以衡量云-ISP链接的网络拥挤，跟踪云 - ISP链接的绩效，以跟踪其在我们的范围内的绩效，以便在美国的范围内进行较大的绩效，并作为其广泛的定位范围内的范围，以及在本地范围内的延伸，并在其范围内降级，并在其范围内进行了范围，并在本地范围内进行了交易，并在其范围内进行了交易，并在本地范围内进行了降级，并在其范围工作场所。 该科学测量项目将解决三个挑战：1）基于拓扑测量和分析的住宅访问和运输ISP中测试服务器的战略选择，2）速度测试算法和行为的科学表征，以及3）正确的解释测量结果。该实验将利用各种商业平台（例如Ookla）部署的速度测试服务器，作为从托管高带宽应用程序的云平台进行吞吐量测量的有利位置。该实验将提供纵向数据，以分析云-ISP互连的性能降解。这项研究将使美国在这一大流行期间在美国关键互联网基础设施的性能和可靠性，通过收集和共享数据来阐明云基远程望远镜应用的质量，从而研究美国关键的Internet基础架构的性能和可靠性。可视化的数据将生成以提供网络性能的纵向视图，并在地理和拓扑上以细粒度识别性能降解。 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.

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