10 minutes 2046 Words
2023-08-01 (Last updated: 2023-08-17 17:52)
b4ee898 @ 2023-08-17
I recently expanded on my Internet map visualization that showed all of the undersea internet cables that run along the bottom of the oceans and seas. This time, I also added dots that represent the locations of all of the advertised internet exchanges in the world. The brighter/greener/bigger the dot, the more bandwidth the internet exchange supports.
And here is the same map but without country borders. I think this one looks beautiful:
What’s an internet exchange?
An internet exchange, often referred to as an Internet Exchange Point (IXP), is a physical infrastructure or facility where Internet Service Providers (ISPs) and other network operators connect their networks together to exchange Internet traffic. The primary purpose of an internet exchange is to improve the efficiency of data exchange between different networks by allowing direct peering between them. Instead of sending data through multiple third-party networks, which can lead to increased latency and costs, ISPs can directly exchange traffic at an internet exchange, resulting in faster and more cost-effective data transmission.
Internet exchanges play a crucial role in the functioning of the global internet. By facilitating direct peering, they help reduce the reliance on expensive long-distance links and enhance the overall performance and resilience of the internet. They also promote competition among ISPs and encourage the growth of internet infrastructure in specific regions.
traceroute command is a network diagnostic tool used to trace the route that data packets take from one computer to another across a network, typically the Internet. It helps identify the network path taken by the data, showing the sequence of intermediate devices (routers) that the packets pass through before reaching the destination.
$ sudo mtr apple.com My traceroute [v0.95] kevins-mbp-m1.local (192.168.88.31) -> apple.com (17.22023-08-02T13:19:54+0200 Keys: Help Display mode Restart statistics Order of fields quit Packets Pings Host Loss% Snt Last Avg Best Wrst StDev 1. router.lan 0.0% 5 5.2 4.8 4.3 5.2 0.4 2. 10.24.0.1 0.0% 4 4.7 4.6 4.3 5.0 0.3 3. soeborg2.net.gigabit.dk 0.0% 4 5.6 6.6 5.5 9.7 2.1 4. apple-1.equinix-am1.nl-ix.net 0.0% 4 15.6 15.5 14.1 16.6 1.0 5. apple.com.sg 0.0% 4 15.2 15.0 14.5 15.6 0.5
In the provided example output:
kevins-mbp-m1.localis the name of the source host or the computer from which the
tracerouteis initiated. That’s my laptop, so I know that it is located in Copenhagen, Denmark.
apple.comis the destination host or the target server to which the
tracerouteis being performed.
The columns in the output represent the following information:
Host: The intermediate routers or nodes in the network path.
Loss%: The percentage of packet loss experienced while reaching each router.
Snt: The number of packets sent to each router.
Last: The last round-trip time taken to reach the router.
Avg: The average round-trip time to reach the router.
Best: The best (minimum) round-trip time to reach the router.
Wrst: The worst (maximum) round-trip time to reach the router.
StDev: The standard deviation of round-trip times to the router.
Identifying Exchange Location using Reverse IP Lookup:
traceroute output, you can sometimes infer the location of an internet exchange based on the names of the intermediate routers. Many internet exchanges are named explicitly to indicate their location. For example, in the provided
traceroute, the router with the name
apple-1.equinix-am1.nl-ix.net suggests that it is associated with the Equinix Amsterdam (AM1) data center connected through the NL-IX internet exchange. So my request was probably handled inside of
Luttenbergweg 4, Amsterdam, Netherlands or… this building:
However, it’s important to note that not all routers or nodes in a traceroute will have such descriptive names. Some routers might be labeled with IP addresses or generic names that do not reveal their location. In such cases, it becomes more challenging to pinpoint the exact location of an internet exchange solely based on the traceroute output. Additionally, the reverse IP lookup method depends on the accuracy and up-to-date information in the IP address registries, and some routers might not be accurately represented.
Because of all of this, we can see the path that is taken when connecting to a server, which I think is really cool. With my example, I can know that it takes around 15.5 milliseconds for my network traffic to reach the Netherlands and I can tell that Apple is peering directly in this facility. You can verify this fact by looking at PeeringDB. Essentially, if you want
apple.com to load faster for your users who are near(ish) to Amsterdam, you may want to run some fiber optic cable to this internet exchange. Put another way, the closer you are to the dots the closer you are to the internet.
Observations from the map
Now here’s the pretty part. Here are close-ups of different parts of the map with some general observations.
How it’s made
First, this is where I got the data from:
- PeeringDB - PeeringDB is a user-driven database that offers information about network interconnection facilities and peering arrangements, supporting network administrators in optimizing Internet connectivity.
- Simple Maps - I used this dataset to geolocate all internet exchanges in PeeringDB using the city and country fields.
- Submarine Cable Map - TeleGeography maintains a database of all major submarine fiber optic cables and their status.
Next, these are the different tools/languages that I used:
- d3-node - a library that helps with running d3 inside of a nodejs environment
- d3-geo - a library that handles translating coordinates for different map projections. I know it’s controversial now, but the Earth isn’t flat. So to make a flat image you have to pick how you are going to translate the globe coordinates onto a map. Despite its flaws, I used the Mercator projection because it is by far the most popular map projection.
- The Go Programming Language - This is my current working language, so it’s what I used to integrate with the PeeringDB API and do some data processing/validation.
- PeeringDB - A library for talking to the PeeringDB API.
The pipeline looks like this:
graph LR submarinecables[Submarine Cable Database] --> node[Node JS Script] peeringdb[PeeringDB] --> golang[Go Script] geocities[Geolocation Database] --> golang[Go Script] golang[Go Script] --> node[Node JS Script] node[Node JS Script] --> svg[SVG] svg[SVG] --> convert[ImageMagick Convert] --> png[PNG] svg[SVG] --> morgify[ImageMagick Morgify] --> jpg[Displate JPG] style svg stroke:#f66,stroke-width:2px,stroke-dasharray: 5, 5; style jpg stroke:#f66,stroke-width:2px,stroke-dasharray: 5, 5; style png stroke:#f66,stroke-width:2px,stroke-dasharray: 5, 5;
Mapping of Cities to lat/long GPS coordinates
I had so many data validation issues when doing this project. I should have expected this more since PeeringDB is user-managed and there’s no validation of the City field.
I had a lot of random issues mapping internet exchanges with their GPS coordinates. First, the geolocation database I was using is not complete. It only has around 43 thousand cities but there are many, many more towns and cities. The way I handled that was to manually map to the closest city that I do have geo coordinates. Additionally, the city field would be misspelled, formatted in a way differently than my database or the name of the city may have changed. This happens a lot because there are usually multiple ways to convert many languages into Latin characters. And sometimes cities just change their names. All-in-all I have 95 internet exchanges that I have had to manually map. I can’t guarantee that they are all correct… but it is good enough. You can see all of the places that I manually mapped on github.
Here are my favorites:
- There were a few exchanges that spelled their city and sometimes the name of the exchange incorrectly. I’ve sent a few emails to make them aware and a few have fixed it!
- There is an exchange named “Example IX” which is obviously just used as an example: entry on PeeringDB
- The accepted Western name for the capital city of Ukraine changed from Kiev to Kyiv due to the efforts of a campaign called KyivNotKiev. There are several internet exchanges still using the old spelling in its address.
Thanks for reading
So far I’m pretty happy with the results of this little project. If I were to work more on this I would want there to be an actual heatmap instead of just drawing dots. I have attempted to do this but it was taking too long to figure out how to properly do it specifically with the node-d3 library. Also, there’s probably a lot of data validation that I could do… but I do feel like it’s not my job to fix this database so I’m probably not going to do that for the sake of a small side project.
The part that is missing still is the terrestrial fiber links. There’s not good public data on those for several reasons, but you can be assured that there are significant backbone fiber optic cables buried nearby almost every major highway and rail line in the US. So imagine lines that nearly mimic the US road system and you’ll have an idea of what that map would look like. That may be the next step for this map since it’s a bit hard to understand that we only have undersea cables.