  YouTube relies on a massively distributed Content Delivery Network (CDN) to
stream the billions of videos in its catalogue. Unfortunately, very little
information about the design of such CDN is available. This, combined with the
pervasiveness of YouTube, poses a big challenge for Internet Service Providers
(ISPs), which are compelled to optimize end-users' Quality of Experience (QoE)
while having no control on the CDN decisions.
  This paper presents YouLighter, an unsupervised technique to identify changes
in the YouTube CDN. YouLighter leverages only passive measurements to cluster
co-located identical caches into edge-nodes. This automatically unveils the
structure of YouTube's CDN. Further, we propose a new metric, called
Constellation Distance, that compares the clustering obtained from two
different time snapshots, to pinpoint sudden changes. While several approaches
allow comparison between the clustering results from the same dataset, no
technique allows to measure the similarity of clusters from different datasets.
Hence, we develop a novel methodology, based on the Constellation Distance, to
solve this problem.
  By running YouLighter over 10-month long traces obtained from two ISPs in
different countries, we pinpoint both sudden changes in edge-node allocation,
and small alterations to the cache allocation policies which actually impair
the QoE that the end-users perceive.
