Association for Computing Machinery
Dynamic Adaptive Streaming over HTTP (DASH) is widely deployed on the Internet for live and on-demand video streaming services. Video adaptation algorithms in existing DASH systems are either too sluggish to respond to congestion level shifts or too sensitive to short-term network bandwidth variations. Both degrade user video experience. In this paper, the authors formally study the responsiveness and smoothness trade-off in DASH through analysis and experiments. They show that client-side buffered video time is a good feedback signal to guide video adaptation. They then propose novel video rate control algorithms that balance the needs for video rate smoothness and high bandwidth utilization. They show that a small video rate margin can lead to much improved smoothness in video rate and buffer size.