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University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  1/2019 - 12
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Adaptive Quality Control Scheme Based on VBR Characteristics to Improve QoE of UHD Streaming Service

KIM, M. See more information about KIM, M. on SCOPUS See more information about KIM, M. on IEEExplore See more information about KIM, M. on Web of Science, CHUNG, K. See more information about CHUNG, K. on SCOPUS See more information about CHUNG, K. on SCOPUS See more information about CHUNG, K. on Web of Science
 
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Download PDF pdficon (1,313 KB) | Citation | Downloads: 927 | Views: 2,764

Author keywords
adaptive control, data transfer, high definition video, quality of service, streaming media

References keywords
streaming(16), communications(12), video(11), adaptation(11), adaptive(9), quality(7), rate(6), experience(6), bitrate(6), tutorials(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-02-28
Volume 19, Issue 1, Year 2019, On page(s): 89 - 98
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.01012
Web of Science Accession Number: 000459986900012
SCOPUS ID: 85064214463

Abstract
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Recently, with the development of networks and smart devices, the demand for Ultra High Definition (UHD) video has risen, and HTTP adaptive streaming has attracted attention. HTTP adaptive streaming can guarantee high Quality of Experience (QoE) because it adaptively selects the video quality according to the network state. However, the existing quality control schemes experience unnecessary quality changes and low average video quality due to the bandwidth measurement and the quality control that do not consider the Variable Bit Rate (VBR) content characteristics of the UHD video. In this paper, we propose an adaptive quality control scheme based on VBR content characteristics to improve QoE of UHD streaming service. The proposed scheme measures the bandwidth using the actual bit rate of the segment and the difference in the network adaptability between segments. Furthermore, the proposed scheme defines a quality control region by considering the buffer state of the client. The quality control region consists of four subregions based on buffer thresholds, and the client selects the quality differently according to each subregion. Experimental results have shown that the proposed scheme improves the QoE compared to the existing schemes by minimizing the unnecessary quality changes and maximizing the average video quality.


References | Cited By  «-- Click to see who has cited this paper

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[2] J. Kua, G. Armitage, and P. Branch, "A Survey of Rate Adaptation Techniques for Dynamic Adaptive Streaming over HTTP," IEEE Communications Surveys & Tutorials, Vol. 19, No. 3, pp. 1842-1866, Mar. 2017.
[CrossRef] [Web of Science Times Cited 201] [SCOPUS Times Cited 237]


[3] Microsoft, "Microsoft Smooth Streaming," 2016. [Online] Available: Temporary on-line reference link removed - see the PDF document

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[CrossRef] [SCOPUS Times Cited 1010]


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[18] H. Nam, K. H. Kim, and H. Schulzrinne, "QoE Matters More Than QoS: Why People Stop Watching Cat Videos," Proc. of the IEEE International Conference on Computer Communications, pp. 1-9, Apr. 2016.
[CrossRef] [SCOPUS Times Cited 99]


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[29] The Network Simulator NS-3, [Online] Available: Temporary on-line reference link removed - see the PDF document



References Weight

Web of Science® Citations for all references: 2,506 TCR
SCOPUS® Citations for all references: 4,228 TCR

Web of Science® Average Citations per reference: 84 ACR
SCOPUS® Average Citations per reference: 141 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-21 11:24 in 152 seconds.




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