Detecting events in the dynamics of ego-centred measurements of the Internet topology

Detecting events such as major routing changes or congestions in the dynamics of the Internet topology is an important but challenging task. We explore here an empirical approach based on a notion of statistically significant events. It consists in identifying properties of graph dynamics which exhibit a homogeneous distribution with outliers, corresponding to events. We apply this approach to ego-centred measurements of the Internet topology (views obtained from a single monitor) and show that it succeeds in detecting meaningful events. Finally, we give some hints for the interpretation of detected events in terms of network operations.