BETA: Bandwidth-efficient temporal adaptation for video streaming over reliable transports

Abstract

To cope with diverse network conditions, HTTP Adaptive Streaming (HAS) enables video players to dynamically change the video quality throughout the video stream. However, effective adaptation that minimizes stalls and start-up time while maximizing quality and stability remains elusive, especially when available bandwidth is variable or multiple players compete for the bottleneck capacity. Conventional approach to adaptation is to make a decision on the next video segment quality based on hysteresis of prior throughput measurements. This approach is not robust to bandwidth fluctuation at small time scales, which can consequently lead to stalls, bandwidth waste, and unstable quality, mainly due to the inability to mitigate significant bandwidth reduction during the segment download. We propose BETA- Bandwidth-Efficient Temporal Adaptation, an agile approach that allows HAS players to refine the quality level within video segments on the fly, according to the actual bandwidth conditions experienced while downloading each segment. We define a new HAS-oriented transmission order of video frames within segments that facilitates decodability of partial frames and paves the way for changing the paradigm from discrete to continuous bitrate ladders for HAS. BETA can work with any adaptation algorithm or HAS player to significantly improve robustness and efficiency in dynamic network environments and for low-latency streams, as well as to dramatically reduce content storage and encoding infrastructure requirements. Our evaluation using the real player implementation shows that BETA improves video quality by up to 20%, reduces number of stalls by 20%-100% in nearly 80% of cases, and cuts down wasted bandwidth by 22%-100%.