Abstract
Video clients employ HTTP-based adaptive bitrate (ABR) algorithms to optimize users’ quality of experience (QoE). ABR algorithms adopt video quality based on the network conditions during playback. The existing state-of-the-art ABR algorithms ignore the fact that video streaming services deploy segment durations differently in different services, and HTTP clients offer distinct buffer sizes. The existing ABR algorithms use fixed control laws and are designed with predefined client/server settings. As a result, adaptation algorithms fail to achieve optimal performance across a variety of video client settings and QoE objectives. We propose a buffer- and segment-aware fuzzy-based ABR algorithm that selects video rates for future video segments based on segment duration and the client’s buffer size in addition to throughput and playback buffer level. We demonstrate that the proposed algorithm guarantees high QoE across various video player settings and video content characteristics. The proposed algorithm efficiently utilizes bandwidth in order to download high-quality video segments and to guarantee high QoE. The results from our experiments reveal that the proposed adaptation algorithm outperforms state-of-the-art algorithms, providing improvements in average video rate, QoE, and bandwidth utilization, respectively, of 5% to 18%, about 13% to 30%, and up to 45%.
Highlights
Multimedia content accounts for the majority of internet traffic
The results from our extensive experiments reveal that the proposed long video adaptation algorithm outperforms state-of-the-art algorithms, with average improvements in video rate, quality of experience (QoE), and bandwidth utilization, respectively, ranging from 5% to 18%, by about 13% to 30%, and by up to 45%
The results indicate that the proposed algorithm guaranteed high QoE irrespective of buffer size, segment duration, and video sequence
Summary
Multimedia content accounts for the majority of internet traffic. According to the. A smaller playback buffer would fill up quickly, compared to a larger buffer This would allow the adaptation algorithms to aggressively increase the video rate. The existing algorithms igBuffer size: 20 seconds, such 2 seconds nore important parameters, as duration: segment duration and the client’s playback buffer size, when selecting video quality. This results in inconsistent performance from algorithms under different settings. As the buffer level increases, the algorithms select the video extensive experiments reveal that the proposed long video adaptation algorithm outperaptation algorithm, and Section 6 presents the simulation results. A larger buffer reduces the risk of playback interruption in case of a mismatch
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
