PhD thesis defense by Matthieu Gouel “Internet-Scale Route Tracing Capture and Analysis”

Speaker : Matthieu Gouel
Date: 12/06/2023
Time: 1:00 pm - 4:00 pm
Location: Jussieu, Room 24-25/405-SOC


The Internet is one of the most remarkable human creations, enabling com-
munication among about two thirds of the global population. This network
of networks spans the entire globe and is managed in a highly decentralized
way, making it impossible to fully comprehend at IP-level. Nonetheless, for
over two decades, researchers have been devising new techniques, developing
new tools, and creating new platforms to capture and provide more precise
and comprehensive maps of the Internet’s topology. These e?orts support
network operators in the industry and other researchers in improving core
features of the Internet such as its connectivity, performance, security, or
This thesis presents new contributions that improve the scalability of
Internet topology measurement. It introduces a state of the art measurement
platform that enables the use of high-speed probing techniques for IP route
tracing at Internet scale, as well as a reinforcement learning approach to
maximize the discovery of the Internet topology. Because the analysis of the
route tracing data collected requires additional metadata, the evolution of
IP address geolocation over a 10-year period in a widely used proprietary
database is examined, and lessons are provided to avoid biases in studies
using this database. Finally, a large-scale analysis framework is developed to
effectively utilize the large number of collected data and augmented metadata
from other sources, such as IP address geolocation, to produce insightful
studies at the Internet scale.
This work aims to considerably improve the study of the Internet topology
by providing tools to collect and analyze large amounts of Internet topology
data. This will allow researchers to better understand how the Internet is
structured and how it evolves over time, leading to a more comprehensive
understanding of this complex system.