Geo Traceroute

Methodology

Methodology

Geolocalisation of routers involved in a traceroute is a complex task, as all available GeoIP databases
(free or commercial) are largely inaccurate for interconnection and backbone router IPs.
The methodology used here relies on an automated inference-based algorithm that replicates the analysis
a human network engineer would perform when inspecting a traceroute.

This includes:

Analyzing reverse DNS names to identify city names and IATA/ICAO airport codes.
Consulting multiple GeoIP databases and checking for consistency.
Analyzing latency to infer the most plausible location and discard implausible results.
Analyzing the path to detect inconsistencies (loops, abnormal routing patterns).
Analyzing the graph and assigning weights to the most likely city based on latency using Bayesian logic.
Relocating hops to a more logical city when an inconsistency is detected.
As a last resort, using machine-learning–assisted reverse DNS parsing to extract city information.

The algorithm operates entirely in real time and does not store any computed results in a database.

This approach is not 100% accurate and never will be.
Based on manual validation across more than 2,000 computed paths,
the observed accuracy is approximately 90% at a city or logical metro-area level.
The remaining 10% mainly involve IPs with missing or misleading reverse DNS entries or abnormal latency behavior.

Salim Gasmi