Improving quality of experience in adaptive low latency live streaming

Lyko, Tomasz; Broadbent, Matthew; Race, Nicholas; Nilsson, Mike; Farrow, Paul; Appleby, Steve

Abstract

HTTP Adaptive Streaming (HAS), the most prominent technology for streaming video over the Internet, suffers from high end-to-end latency when compared to conventional broadcast methods. This latency is caused by the content being delivered as segments rather than as a continuous stream, requiring the client to buffer significant amounts of data to provide resilience to variations in network throughput and enable continuous playout of content without stalling. The client uses an Adaptive Bitrate (ABR) algorithm to select the quality at which to request each segment to trade-off video quality with the avoidance of stalling to improve the Quality of Experience (QoE). The speed at which the ABR algorithm responds to changes in network conditions influences the amount of data that needs to be buffered, and hence to achieve low latency the ABR needs to respond quickly. Llama (Lyko et al. 28) is a new low latency ABR algorithm that we have previously proposed and assessed against four on-demand ABR algorithms. In this article, we report an evaluation of Llama that demonstrates its suitability for low latency streaming and compares its performance against three state-of-the-art low latency ABR algorithms across multiple QoE metrics and in various network scenarios. Additionally, we report an extensive subjective test to assess the impact of variations in video quality on QoE, where the variations are derived from ABR behaviour observed in the evaluation, using short segments and scenarios. We publish our subjective testing results in full and make our throughput traces available to the research community.

Citation

Lyko, T., Broadbent, M., Race, N., Nilsson, M., Farrow, P., & Appleby, S. (2024). Improving quality of experience in adaptive low latency live streaming. Multimedia Tools and Applications, 83, 15957-15983. https://doi.org/10.1007/s11042-023-15895-9

• Journal Article Type: Article
• Acceptance Date: May 22, 2023
• Online Publication Date: Jul 12, 2023
• Publication Date: 2024
• Deposit Date: Jul 17, 2023
• Publicly Available Date: Jul 17, 2023
• Journal: Multimedia Tools and Applications
• Print ISSN: 1380-7501
• Electronic ISSN: 1573-7721
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 83
• Pages: 15957-15983
• DOI: https://doi.org/10.1007/s11042-023-15895-9
• Keywords: CMAF, DASH, ABR algorithm, Live streaming, Low latency, Quality of Experience, Video quality assessment, Database
• Public URL: http://researchrepository.napier.ac.uk/Output/3144969