Feedback control for adaptive live video streaming

TLDR

Multimedia content drives a growing share of Internet traffic, with video streaming as a key contributor, and adaptive streaming improves upon classic progressive download by dynamically adjusting bitrate to match bandwidth and maintain quality. The authors propose a Quality Adaptation Controller (QAC) for live adaptive video streaming that applies feedback control theory. QAC employs a feedback controller to adjust the video bitrate in real time, aiming for maximum quality of experience while ensuring continuous playback, and its performance was experimentally compared against Akamai’s adaptive streaming. Experiments show that QAC can match available bandwidth within 30 s, maintains continuous playback, fairly shares bandwidth with concurrent TCP or video flows, whereas Akamai underutilizes bandwidth and suffers interruptions during abrupt bandwidth drops.

Abstract

Multimedia content feeds an ever increasing fraction of the Internet traffic. Video streaming is one of the most important applications driving this trend. Adaptive video streaming is a relevant advancement with respect to classic progressive download streaming such as the one employed by YouTube. It consists in dynamically adapting the content bitrate in order to provide the maximum Quality of Experience, given the current available bandwidth, while ensuring a continuous reproduction. In this paper we propose a Quality Adaptation Controller (QAC) for live adaptive video streaming designed by employing feedback control theory. An experimental comparison with Akamai adaptive video streaming has been carried out. We have found the following main results: 1) QAC is able to throttle the video quality to match the available bandwidth with a transient of less than 30s while ensuring a continuous video reproduction; 2) QAC fairly shares the available bandwidth both in the cases of a concurrent TCP greedy connection or a concurrent video streaming flow; 3) Akamai underutilizes the available bandwidth due to the conservativeness of its heuristic algorithm; moreover, when abrupt available bandwidth reductions occur, the video reproduction is affected by interruptions.