User-perceived QoE Improvement by Differentiated ECN based on Video Semantics

A video streaming user is usually interested in some semantically-important scenes of a video content, e.g. goal scene in a football game. If the user could watch the video segments consisting that scene with high quality, the quality of experience (QoE) of the user would be substantially improved more than ever. Although Adaptive Bitrate (ABR) algorithm considering this aspect can achieve better QoE, design of current approach has been limited only inside the application layer. It is expected that higher QoE could be achieved when the underlying transport layer also handle these semantics information for its congestion control mechanism. In this paper, we propose a new concept for quality of service (QoS) control with differentiated explicit congestion notification (ECN) to improve QoE and reveal that throughput differentiation by ECN considering video semantics can improve QoE of a video streaming user. Evaluation results show that throughput differentiation by congestion control conducted inside the network improves the QoE of the user up to 57.9%.