Efficient QoE-Aware Scheme for Video Quality Switching Operations in Dynamic Adaptive Streaming

Author:

Irondi Iheanyi1,Wang Qi1ORCID,Grecos Christos2,Calero Jose M. Alcaraz1,Casaseca-De-La-Higuera Pablo3

Affiliation:

1. University of the West of Scotland, United Kingdom

2. Central Washington University, Ellensburg, WA, USA

3. University of the West of Scotland, and Universidad de Valladolid, Valladolid, Spain

Abstract

Dynamic Adaptive Streaming over HTTP (DASH) is a popular over-the-top video content distribution technique that adapts the streaming session according to the user's network condition typically in terms of downlink bandwidth. This video quality adaptation can be achieved by scaling the frame quality, spatial resolution or frame rate. Despite the flexibility on the video quality scaling methods, each of these quality scaling dimensions has varying effects on the Quality of Experience (QoE) for end users. Furthermore, in video streaming, the changes in motion over time along with the scaling method employed have an influence on QoE, hence the need to carefully tailor scaling methods to suit streaming applications and content type. In this work, we investigate an intelligent DASH approach for the latest video coding standard H.265 and propose a heuristic QoE-aware cost-efficient adaptation scheme that does not switch unnecessarily to the highest quality level but rather stays temporarily at an intermediate quality level in certain streaming scenarios. Such an approach achieves a comparable and consistent level of quality under impaired network conditions as commonly found in Internet and mobile networks while reducing bandwidth requirements and quality switching overhead. The rationale is based on our empirical experiments, which show that an increase in bitrate does not necessarily mean noticeable improvement in QoE. Furthermore, our work demonstrates that the Signal-to-Noise Ratio (SNR) and the spatial resolution scalability types are the best fit for our proposed algorithm. Finally, we demonstrate an innovative interaction between quality scaling methods and the polarity of switching operations. The proposed QoE-aware scheme is implemented and empirical results show that it is able to reduce bandwidth requirements by up to 41% whilst achieving equivalent QoE compared with a representative DASH reference implementation.

Funder

UK Royal Society of Edinburgh and National Science Foundation of China

European Commission Horizon 2020 5G-PPP Programs

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. EQMS: An improved energy-aware and QoE-aware video streaming policy across multiple competitive mobile devices;Wireless Networks;2022-12-19

2. Bi-criteria Approximation for a Multi-origin Multi-channel Auto-scaling Live Streaming Cloud;IEEE Transactions on Multimedia;2022

3. Reinforcement Learning Based Dynamic Adaptive Video Streaming for Multi-client over NDN;2021 4th International Conference on Hot Information-Centric Networking (HotICN);2021-11-25

4. Game Theory Based Dynamic Adaptive Video Streaming for Multi-client over NDN;IEEE Transactions on Multimedia;2021

5. Multi-User Competitive Energy-Aware and QoE-Aware Video Streaming on Mobile Devices;Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks;2020-11-16

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