YouLighter: A Cognitive Approach to Unveil YouTube CDN and Changes

摘要

YouTube relies on a massively distributed content delivery network (CDN) to stream the billions of videos in its catalog. 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 almost no visibility and understanding of CDN decisions. This paper presents YouLighter, an unsupervised technique that builds upon cognitive methodologies to identify changes in how the YouTube CDN serves traffic. YouLighter leverages only passive measurements and clustering algorithms to group caches that appear colocated and identical into edge-nodes. This automatically unveils the YouTube edge-nodes used by the ISP customers. Next, we leverage a new metric, called Pattern Dissimilarity, that compares the clustering results obtained from two different time snapshots to pinpoint sudden changes. 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