HTTP Adaptive Video Streaming and Quality of Experience
Michael Seufert, Chair of Communication Networks, Julius-Maximilians Universität Würzburg
Changing network conditions, especially in mobile networks, pose severe problems to video streaming in the Internet. HTTP adaptive streaming (HAS) is a technology employed by numerous video services that relieves these issues by adapting the video to the current network conditions. It enables service providers to improve resource utilization and Quality of Experience (QoE) by incorporating information from different layers in order to deliver and adapt a video in its best possible quality. Thereby, it allows taking into account end user device capabilities, available video quality levels, current network conditions, and current server load. For end users, the major benefits of HAS compared to classical HTTP video streaming are reduced interruptions of the video playback and higher bandwidth utilization, which both generally result in a higher QoE. Adaptation is possible by changing the frame rate, resolution, or quantization of the video, which can be done with various adaptation strategies and related client- and server-side actions.
This tutorial gives an overview of the current state of the art and recent developments. At the same time, it targets networking researchers, who develop new solutions for HTTP video streaming or assess video streaming from a user centric point of view. Therefore, it is structured into two parts:
The first part of the tutorial will focus on the technical development of HAS, existing open standardized solutions, but also proprietary solutions. This understanding is fundamental to derive the QoE influence factors that emerge as a result of adaptation. The second part of the tutorial will present QoE related works from human computer interaction and networking domains, which are structured according to the QoE impact of video adaptation. To be more precise, subjective studies that cover QoE aspects of adaptation dimensions and strategies are revisited. As a result, QoE influence factors of HAS and corresponding QoE models are identified, but also open issues and conflicting results are discussed. Furthermore, technical influence factors, which are often ignored in the context of HAS, affect perceptual QoE influence factors and are consequently analyzed.
Michael Seufert studied computer science, mathematics, and education at the University of Würzburg, Germany. In 2011, he received the Diploma degree in computer science, and additionally passed the first state examinations for teaching mathematics and computer science in secondary schools. From 2012-2013, he was with FTW Telecommunication Research Center Vienna, Austria, working in the area of user-centered interaction and communication economics. He is currently a Researcher at the Chair of Communication Networks, University of Würzburg, where he is working toward the Ph.D. degree. His research mainly focuses on QoE of Internet applications, social networks, performance modeling and analysis, and traffic management solutions.