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YouTube relies on a massively distributed Content Delivery Network (CDN) tostream the billions of videos in its catalogue. Unfortunately, very littleinformation about the design of such CDN is available. This, combined with thepervasiveness 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 changesin the YouTube CDN. YouLighter leverages only passive measurements to clusterco-located identical caches into edge-nodes. This automatically unveils thestructure of YouTube's CDN. Further, we propose a new metric, calledConstellation Distance, that compares the clustering obtained from twodifferent time snapshots, to pinpoint sudden changes. While several approachesallow comparison between the clustering results from the same dataset, notechnique allows to measure the similarity of clusters from different datasets.Hence, we develop a novel methodology, based on the Constellation Distance, tosolve this problem.  By running YouLighter over 10-month long traces obtained from two ISPs indifferent countries, we pinpoint both sudden changes in edge-node allocation,and small alterations to the cache allocation policies which actually impairthe QoE that the end-users perceive.

YouLighter: An Unsupervised Methodology to Unveil YouTube CDN Changes