A Radar for the Internet

TL;DR

This paper introduces a radar-like measurement approach to study individual machines' ego-centered views of internet topology, providing long-term data and event detection capabilities.

Contribution

It presents a novel ego-centered measurement tool and methodology for dynamic internet topology analysis, differing from traditional comprehensive mapping.

Findings

Collected long-term, high-frequency ego-centered topology data

Demonstrated the ability to detect internet topology events

Provided a dataset for further analysis of internet dynamics

Abstract

In contrast with most internet topology measurement research, our concern here is not to obtain a map as complete and precise as possible of the whole internet. Instead, we claim that each machine's view of this topology, which we call ego-centered view, is an object worth of study in itself. We design and implement an ego-centered measurement tool, and perform radar-like measurements consisting of repeated measurements of such views of the internet topology. We conduct long-term (several weeks) and high-speed (one round every few minutes) measurements of this kind from more than one hundred monitors, and we provide the obtained data. We also show that these data may be used to detect events in the dynamics of internet topology.