engleski

YouTube QoE Classification Based on Monitoring of Encrypted Traffic

With the move to traffic encryption adopted by many Over The Top (OTT) providers of video distribution services, Internet Service Providers (ISPs) are now facing the challenges of monitoring application performance and potential end user perceived service quality degradations. With lack of direct feedback from OTT providers, ISPs generally rely on passive traffic monitoring solutions deployed within their network for the purposes of monitoring OTT service performance. The aim of this research is to develop tools and methodologies that enable the estimation of end user QoE when watching YouTube videos using different platforms and access networks, based solely on the analysis of encrypted network traffic.

QoE estimation ; client-side monitoring ; YouTube ; machine learning ; encrypted traffic

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