October 2009

A different way to look at the network

Since the middle of August the crawler has been recording the time when hubs join and leave the network. This allows for certain time based trends to be realized. The hub is identified by its IP address. One way to visualize a set of IP addresses is with the Hilbert curve which was made popular by xkcd. The tool I used is called ipv4-heatmap. By generating a heatmap every 2 hours and then playing the images in order a time lapse video is produced. This video will show when users in different parts of the world are online depending on the time of day and the day of the week.

Direct download (3.0 MB, MKV)

Here is a rough breakdown of what the video shows:

  • On the right side half way up is where a lot of Brazilian users are.
  • Above them is where a lot of Asian IPs are.
  • In the bottom left is where Europe is.
  • In the center left and the top center is North America.

Consult the ipv4-heatmap website for more details on IP distribution or the slightly outdated internet map from xkcd.

Thanks to Daisuke from irc.p2pchat.net #shareaza for his excellent work converting the images to a video.


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Two new experimental features

A few weeks ago two new features were released. The first is a world map view of the country page and the second shows how the network size changes over time.

World Map

The world map shows two different data sets. Red circles represent where hubs say they are located. The size of the circle indicates how many hubs are reported to be at that location. Green circles represent how many hubs are in that country based on their IP address and mapping it to a country using Maxmind’s GeoIP. The location of the green circle is either drawn roughly in the center of the country it represents or at the country’s capital. The country location data was collected from Freebase.com.

Network size changes

The network size page shows graphically how the network size is changing. Each data point shows how many hubs or leaves joined or departed the network from the previous network measurement. So for example if one data point reads +200 hubs then 200 hubs joined the network between that time and the last network measurement.

This also is the debut of pChart usage on the crawler website. It makes creating beautiful and useful graphs easy. I look forward to using it more in the future.


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