Categories
Papers Publications

new symposium paper “Visualizing Internet Measurements of Covid-19 Work-from-Home” at IEEE Symposium on REU Research in Data Science, Systems, and Security

We published a new paper “Visualizing Internet Measurements of Covid-19 Work-from-Home” by Erica Stutz (Swarthmore College), Yuri Pradkin, Xiao Song, and John Heidemann (USC/ISI) at the Symposium for REU Research in Data Science, Systems, and Security, co-located with IEEE BigData 2021.

A screenshot from our Covid-WFH website showing an event in Malaysia on 2020-04-02.
A change in Internet use seen in Malaysia on 2020-04-02, present in our Covid-WFH data but discovered through our website.

From the abstract:

The Covid-19 pandemic disrupted the world as businesses and schools shifted to work-from-home (WFH), and comprehensive maps have helped visualize how those policies changed over time and in different places. We recently developed algorithms that infer the onset of WFH based on changes in observed Internet usage. Measurements of WFH are important to evaluate how effectively policies are implemented and followed, or to confirm policies in countries with less transparent journalism.This paper describes a web-based visualization system for measurements of Covid-19-induced WFH. We build on a web-based world map, showing a geographic grid of observations about WFH. We extend typical map interaction (zoom and pan, plus animation over time) with two new forms of pop-up information that allow users to drill-down to investigate our underlying data.We use sparklines to show changes over the first 6 months of 2020 for a given location, supporting identification and navigation to hot spots. Alternatively, users can report particular networks (Internet Service Providers) that show WFH on a given day.We show that these tools help us relate our observations to news reports of Covid-19-induced changes and, in some cases, lockdowns due to other causes. Our visualization is publicly available at https://covid.ant.isi.edu, as is our underlying data.

Datasets from this work will be available from our website and can be seen now at https://covid.ant.isi.edu. We thank NSF grants 2028279 and CNS-2007106 for supporting this work.

Categories
Announcements Projects

new project “Measuring the Internet during Novel Coronavirus to Evaluate Quarantine” (MINCEQ)

We are happy to announce a new project “Measuring the Internet during Novel Coronavirus to Evaluate Quarantine” (MINCEQ).

Measuring the Internet during Novel Coronavirus to Evaluate Quarantine (RAPID-MINCEQ) is a project to measure changes in Internet use during the COVID-19 outbreak of 2020. As the world grapples with COVID-19, work-from-home and study-from-home are widely employed. Implementation of these policies varies across the U.S. and globally due to local circumstances. A common consequence is a huge shift in Internet use, with schools and workplaces emptying and home Internet use increasing. The goal of this project is to observe this shift, globally, through changes in Internet address usage, allowing observation of early reactions to COVID and, one hopes, a future shift back.

This project plans to develop two complementary methods of assessing Internet use by measuring address activity and how it changes relative to historical trends. The project will directly measure Internet address use globally based on continuous, ongoing measurements of more than 4 million IPv4 networks. The project will also directly measure Internet address use in network traffic at a regional Internet exchange point where multiple Internet providers interconnect. The first approach provides a global picture, while the second provides a more detailed but regional picture; together they will help evaluate measurement accuracy.

The project website is at https://ant.isi.edu/minceq/index.html. The PI is John Heidemann. This work is supported by NSF as a RAPID award in response to COVID-19, award NSF-2028279.