Who to blame when YouTube is not working? detecting anomalies in CDN-provisioned services

Abstract

Internet-scale services like YouTube are provisioned by large Content Delivery Networks (CDNs), which push content as close as possible to the end-users to improve their Quality of Experience (QoE) and to pursue their own optimization goals. Adopting space and time variant traffic delivery policies, CDNs serve users' requests from multiple servers/caches at different physical locations and different times. CDNs traffic distribution policies can have a relevant impact on the traffic routed through the Internet Service Provider (ISP), as well as unexpected negative effects on the end-user QoE. In the event of poor QoE due to faulty CDN server selection, a major problem for the ISP is to avoid being blamed by its customers. In this paper we show a real case study in which Google CDN server selection policies negatively impact the QoE of the customers of a major European ISP watching YouTube. We argue that it is extremely important for the ISP to rapidly and automatically detect such events to increase its visibility on the overall operation of the network, as well as to promptly answer possible customer complaints. We therefore present an Anomaly Detection (AD) system for detecting unexpected cache-selection changes in the traffic delivered by CDNs. The proposed algorithm improves over traditional AD approaches by analyzing the complete probability distribution of the monitored features, as well as by self-adapting its functioning to dynamic environments, providing better detection capabilities.