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

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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.