Data-driven QoE analysis on video streaming in mobile networks

Qingyong Wang; Hong Ning Dai; Hao Wang; Di Wu

doi:10.1109/ISPA/IUCC.2017.00168

Data-driven QoE analysis on video streaming in mobile networks

Qingyong Wang, Hong Ning Dai, Hao Wang, Di Wu

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

7 Citations (Scopus)

Abstract

There is a substantial body of literature on analyzing Quality of Experience (QoE) of Video Streaming while there are few studies on standardizing QoE assessments. One of recent proposals on standardizing QoE of video streaming is video Mean Opinion Score (vMOS), which can model QoE of video streaming in 5 discrete grades. However, there are few studies on quantifying vMOS and investigating the relation between vMOS and other Quality of Service (QoS) parameters. In this paper, we address this concern by proposing a data-driven QoE analysis framework on video streaming QoE data. Moreover, we conduct extensive experiments on realistic dataset and verify the effectiveness of our proposed model. Our results show that vMOS is essentially affected by many QoS parameters such as initial buffering latency, stalling ratio and stalling times. Interestingly, we have found that a small set of QoS parameters play an important role in determining vMOS.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
Editors	Guojun Wang, Geoffrey Fox, Gregorio Martinez, Richard Hill, Peter Mueller
Publisher	IEEE
Pages	1115-1121
Number of pages	7
ISBN (Electronic)	9781538637906
ISBN (Print)	9781538637913
DOIs	https://doi.org/10.1109/ISPA/IUCC.2017.00168
Publication status	Published - Dec 2017
Event	15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 - Guangzhou, China Duration: 12 Dec 2017 → 15 Dec 2017 https://ieeexplore.ieee.org/xpl/conhome/8360389/proceeding

Publication series

Name	Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

Conference

Conference	15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
Country/Territory	China
City	Guangzhou
Period	12/12/17 → 15/12/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8360389/proceeding

Scopus Subject Areas

Computer Science Applications
Hardware and Architecture
Information Systems
Control and Optimization
Computer Networks and Communications

User-Defined Keywords

Mobile Networks
Quality of Experience-(QoE)
Quality of Service-(QoS)
Video Streaming

Access to Document

10.1109/ISPA/IUCC.2017.00168

Cite this

Wang, Q., Dai, H. N., Wang, H., & Wu, D. (2017). Data-driven QoE analysis on video streaming in mobile networks. In G. Wang, G. Fox, G. Martinez, R. Hill, & P. Mueller (Eds.), Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 (pp. 1115-1121). (Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)). IEEE. https://doi.org/10.1109/ISPA/IUCC.2017.00168

Wang, Qingyong ; Dai, Hong Ning ; Wang, Hao et al. / Data-driven QoE analysis on video streaming in mobile networks. Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. editor / Guojun Wang ; Geoffrey Fox ; Gregorio Martinez ; Richard Hill ; Peter Mueller. IEEE, 2017. pp. 1115-1121 (Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)).

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title = "Data-driven QoE analysis on video streaming in mobile networks",

abstract = "There is a substantial body of literature on analyzing Quality of Experience (QoE) of Video Streaming while there are few studies on standardizing QoE assessments. One of recent proposals on standardizing QoE of video streaming is video Mean Opinion Score (vMOS), which can model QoE of video streaming in 5 discrete grades. However, there are few studies on quantifying vMOS and investigating the relation between vMOS and other Quality of Service (QoS) parameters. In this paper, we address this concern by proposing a data-driven QoE analysis framework on video streaming QoE data. Moreover, we conduct extensive experiments on realistic dataset and verify the effectiveness of our proposed model. Our results show that vMOS is essentially affected by many QoS parameters such as initial buffering latency, stalling ratio and stalling times. Interestingly, we have found that a small set of QoS parameters play an important role in determining vMOS.",

keywords = "Mobile Networks, Quality of Experience-(QoE), Quality of Service-(QoS), Video Streaming",

author = "Qingyong Wang and Dai, {Hong Ning} and Hao Wang and Di Wu",

note = "Funding Information: ACKNOWLEDGEMENT The work described in this paper was partially supported by Macao Science and Technology Development Fund under Grant No. 096/2013/A3, the National Key R&D Program of China under Grant 2016YFB0201900, the National Natural Science Foundation of China under Grant 61572538 and Grant 61672170, the Fundamental Research Funds for the Central Universities under Grant 17LGJC23, and the Science and Technology Planning Project of Guangdong Province (No. 2017A050501035). The authors would like to express their appreciation for Gordon K.-T. Hon for his thoughtful discussions. Publisher Copyright: {\textcopyright} 2017 IEEE.; 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",

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booktitle = "Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017",

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Wang, Q, Dai, HN, Wang, H & Wu, D 2017, Data-driven QoE analysis on video streaming in mobile networks. in G Wang, G Fox, G Martinez, R Hill & P Mueller (eds), Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC), IEEE, pp. 1115-1121, 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017, Guangzhou, China, 12/12/17. https://doi.org/10.1109/ISPA/IUCC.2017.00168

Data-driven QoE analysis on video streaming in mobile networks. / Wang, Qingyong; Dai, Hong Ning; Wang, Hao et al.
Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. ed. / Guojun Wang; Geoffrey Fox; Gregorio Martinez; Richard Hill; Peter Mueller. IEEE, 2017. p. 1115-1121 (Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Data-driven QoE analysis on video streaming in mobile networks

AU - Wang, Qingyong

AU - Dai, Hong Ning

AU - Wang, Hao

AU - Wu, Di

N1 - Funding Information: ACKNOWLEDGEMENT The work described in this paper was partially supported by Macao Science and Technology Development Fund under Grant No. 096/2013/A3, the National Key R&D Program of China under Grant 2016YFB0201900, the National Natural Science Foundation of China under Grant 61572538 and Grant 61672170, the Fundamental Research Funds for the Central Universities under Grant 17LGJC23, and the Science and Technology Planning Project of Guangdong Province (No. 2017A050501035). The authors would like to express their appreciation for Gordon K.-T. Hon for his thoughtful discussions. Publisher Copyright: © 2017 IEEE.

PY - 2017/12

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N2 - There is a substantial body of literature on analyzing Quality of Experience (QoE) of Video Streaming while there are few studies on standardizing QoE assessments. One of recent proposals on standardizing QoE of video streaming is video Mean Opinion Score (vMOS), which can model QoE of video streaming in 5 discrete grades. However, there are few studies on quantifying vMOS and investigating the relation between vMOS and other Quality of Service (QoS) parameters. In this paper, we address this concern by proposing a data-driven QoE analysis framework on video streaming QoE data. Moreover, we conduct extensive experiments on realistic dataset and verify the effectiveness of our proposed model. Our results show that vMOS is essentially affected by many QoS parameters such as initial buffering latency, stalling ratio and stalling times. Interestingly, we have found that a small set of QoS parameters play an important role in determining vMOS.

AB - There is a substantial body of literature on analyzing Quality of Experience (QoE) of Video Streaming while there are few studies on standardizing QoE assessments. One of recent proposals on standardizing QoE of video streaming is video Mean Opinion Score (vMOS), which can model QoE of video streaming in 5 discrete grades. However, there are few studies on quantifying vMOS and investigating the relation between vMOS and other Quality of Service (QoS) parameters. In this paper, we address this concern by proposing a data-driven QoE analysis framework on video streaming QoE data. Moreover, we conduct extensive experiments on realistic dataset and verify the effectiveness of our proposed model. Our results show that vMOS is essentially affected by many QoS parameters such as initial buffering latency, stalling ratio and stalling times. Interestingly, we have found that a small set of QoS parameters play an important role in determining vMOS.

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KW - Video Streaming

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T3 - Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)

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Wang Q, Dai HN, Wang H, Wu D. Data-driven QoE analysis on video streaming in mobile networks. In Wang G, Fox G, Martinez G, Hill R, Mueller P, editors, Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. IEEE. 2017. p. 1115-1121. (Proceedings - IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and Communications (ISPA/IUCC)). doi: 10.1109/ISPA/IUCC.2017.00168

Data-driven QoE analysis on video streaming in mobile networks

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