Data diet pills: in-network video quality control system for traffic usage reduction

Abstract

Traffic reduction for bandwidth-hungry video streaming services, such as YouTube, benefits not only subscribers struggling to avoid going over their contracted data limit, but also service providers when the number of people who use video streaming services increase. Because not all stakeholders who want to reduce traffic usage are willing to conduct cumbersome operations, e.g., manually setting lower resolution, we argue here that network operators should introduce a traffic pacer for providing traffic reduction services as an optional plan for subscribers. This paper proposes NetPacer, an in-network traffic pacing system for reducing traffic usage by degrading the video quality. NetPacer has two features. The first is relative pacing, which degrades the video quality relative to the initial quality by traffic shaping, thus enabling flexible quality control. The second is in-network timely video quality identification via encrypted traffic analysis by using machine learning. Through experiments, we demonstrate that NetPacer successfully reduces traffic by 30.8% by degrading the resolution by one level while keeping the QoE (i.e., Mean Opinion Score (MOS)) degradation below 0.268 points on average for 50 YouTube videos.