Introduction

We investigated various PingER metrics derived from the ping measurements made from SLAC,  The most sensitive to this type of disruption appeared to be IPDV.

Using PingER data and comparing the various metrics it provides (including average Round Trip Time (RTT), Conditional Loss Probability (CLP). Inter Packet Delay Variability IPDV), Inter Quartile Range (IQR) of the round trip times, and derived throughput (see Tutorial on Internet Monitoring and Pinger at SLAC), we ascertained that the most stable and yet sensitive metric in detecting changes caused by  Covid-19 interventions was the Inter Packet Delay Variation (IPDV). The data below are for 120 days starting around January 16th and ending around May 14th, 2020. For each country, there is 1 point per day. Only weekday data is shown in order to reduce the variability of the data and to focus more on the effect of interventions such as closing the workplaces, schools, universities, people working from home, or being out of work. The weekday was determined based on the Universal Time  Coordinated (UTC).

The data was divided up by region in order to reduce the number of countries in a single chart. This is done so as to allow separation by eyeball of the IPDV lines for the various countries in a chosen region. It also keeps the data more self-consistent in terms of time zones, development, economy, customs etc. For each region, we show one or more charts of the daily median IPDV. The intervention data is from Wikipedia (e.g. https://en.wikipedia.org/wiki/COVID-19_pandemic_in_Egypt).

We are looking for a significant rise or fall in IPDV possibly correlated with an intervention or growth in cases. The links below point to charts of the IPDV (x-axis in msec.) versus the date. As mentioned above we only show data for the weekdays and there is no data for 1/30/20 thru 2/2/20 (n.b. 2/1/30-2/2/30 are weekends).

There are two Excel spread sheets for the weekday filtered data (two files since the master ran out of tabs): 

• Master most of the anaysis for ipdv 120days weekday data
• Overflow remainder of analysis 

There are two Excel spread sheets for the weekday filtered data (two files since the master ran out of tabs): 

• Master most of the anaysis for ipdv 120days weekday data
• Overflow remainder of analysis 

Note that unless otherwise noted the charts in the above spreadsheet are for weekdays.

Results by region

Asia

E Asia

Africa

Central Africa

East Africa

North Africa

South Africa

West Africa

America

Caribbean

Central America

North America (to be analyzed)

South America

Europe

Baltics

Balkans

Eastern Europe

Northern Europe

Southern Europe

Western Europe

UK and Ireland

Summary

Since PingER was originally set up for monitoring connections between High Energy Physics (HEP) sites that were mainly in the US, Europe and Japan, these regions tend to have hosts that are mainly research or educational. As such they often have high-performance network links as opposed to public network links. See, for example the analysis for Spain and Italy, two countries that were badly impacted by Covid-19.

Possible Future work

Compare weekday usage with allweek usage to see if it makes a notable difference in identifying correlations between PingER and Covid-19. DONE

Rather than use weekdays use midweek (Tue -Thur) to ensure the data avoids weekends. DONE

For each country select the type of target based on:

• is the  connection to SLAC the connection a lightly loaded high-performance link (e.g. using ESnet, Internet2, DANTE, TENET etc),
• is the target host in an educational, commercial, government, organization, or unknown establishment.