A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming

Xiaolin Deng; Liang Chen; Fei Wang; Zesong Fei; Wei Bai; Chen Chi; Guanglin Han; Lei Wan

doi:10.1109/VTCFall.2014.6965834

A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming

Xiaolin Deng, Liang Chen, Fei Wang, Zesong Fei, Wei Bai, Chen Chi, Guanglin Han, Lei Wan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

10 Citations (Scopus)

Abstract

For the popularity of delivering video service over HTTP Adaptive Streaming (HAS) in the mobile network, developing an automatic method to evaluate customers' quality of experience (QoE) for HAS video service in real time is highly desired for network operators and content providers. This paper proposes a novel QoE evaluation strategy for HAS video service based on the specific features of HAS and data-mining technology. Via capturing the media description files of HAS and the request information of clients, the QoE can be monitored in real time for operators. The evaluation algorithm for the proposed strategy is trained and tested based on the data sets collected from subjective test results. The test results suggest that the predicted Mean Opinion Score (pMOS) measured by our evaluation algorithm has high correlation with the Mean Opinion Score (MOS) measured by the subjective test, and meanwhile the evaluation strategy is easy to implement for operators.

Original language	English
Title of host publication	2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479944491, 9781479944491
DOIs	https://doi.org/10.1109/VTCFall.2014.6965834
Publication status	Published - 24 Nov 2014
Event	80th IEEE Vehicular Technology Conference, VTC 2014-Fall - Vancouver, Canada Duration: 14 Sept 2014 → 17 Sept 2014

Publication series

Name	IEEE Vehicular Technology Conference
ISSN (Print)	1550-2252

Conference

Conference	80th IEEE Vehicular Technology Conference, VTC 2014-Fall
Country/Territory	Canada
City	Vancouver
Period	14/09/14 → 17/09/14

Keywords

HTTP Adaptive Streaming (HAS)
MOS (Mean Opinion Score)
Quality of experience (QoE)
data mining
pMOS (predicted Mean Opinion Score)

Access to Document

10.1109/VTCFall.2014.6965834

Cite this

Deng, X., Chen, L., Wang, F., Fei, Z., Bai, W., Chi, C., Han, G., & Wan, L. (2014). A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming. In 2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings Article 6965834 (IEEE Vehicular Technology Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCFall.2014.6965834

@inproceedings{ceff1ab92a1347ef8a5448cc13e37480,

title = "A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming",

abstract = "For the popularity of delivering video service over HTTP Adaptive Streaming (HAS) in the mobile network, developing an automatic method to evaluate customers' quality of experience (QoE) for HAS video service in real time is highly desired for network operators and content providers. This paper proposes a novel QoE evaluation strategy for HAS video service based on the specific features of HAS and data-mining technology. Via capturing the media description files of HAS and the request information of clients, the QoE can be monitored in real time for operators. The evaluation algorithm for the proposed strategy is trained and tested based on the data sets collected from subjective test results. The test results suggest that the predicted Mean Opinion Score (pMOS) measured by our evaluation algorithm has high correlation with the Mean Opinion Score (MOS) measured by the subjective test, and meanwhile the evaluation strategy is easy to implement for operators.",

keywords = "HTTP Adaptive Streaming (HAS), MOS (Mean Opinion Score), Quality of experience (QoE), data mining, pMOS (predicted Mean Opinion Score)",

author = "Xiaolin Deng and Liang Chen and Fei Wang and Zesong Fei and Wei Bai and Chen Chi and Guanglin Han and Lei Wan",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 80th IEEE Vehicular Technology Conference, VTC 2014-Fall ; Conference date: 14-09-2014 Through 17-09-2014",

year = "2014",

month = nov,

day = "24",

doi = "10.1109/VTCFall.2014.6965834",

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Deng, X, Chen, L , Wang, F , Fei, Z, Bai, W, Chi, C, Han, G & Wan, L 2014, A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming. in 2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings., 6965834, IEEE Vehicular Technology Conference, Institute of Electrical and Electronics Engineers Inc., 80th IEEE Vehicular Technology Conference, VTC 2014-Fall, Vancouver, Canada, 14/09/14. https://doi.org/10.1109/VTCFall.2014.6965834

A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming. / Deng, Xiaolin; Chen, Liang ; Wang, Fei et al.
2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 6965834 (IEEE Vehicular Technology Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming

AU - Deng, Xiaolin

AU - Chen, Liang

AU - Wang, Fei

AU - Fei, Zesong

AU - Bai, Wei

AU - Chi, Chen

AU - Han, Guanglin

AU - Wan, Lei

PY - 2014/11/24

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N2 - For the popularity of delivering video service over HTTP Adaptive Streaming (HAS) in the mobile network, developing an automatic method to evaluate customers' quality of experience (QoE) for HAS video service in real time is highly desired for network operators and content providers. This paper proposes a novel QoE evaluation strategy for HAS video service based on the specific features of HAS and data-mining technology. Via capturing the media description files of HAS and the request information of clients, the QoE can be monitored in real time for operators. The evaluation algorithm for the proposed strategy is trained and tested based on the data sets collected from subjective test results. The test results suggest that the predicted Mean Opinion Score (pMOS) measured by our evaluation algorithm has high correlation with the Mean Opinion Score (MOS) measured by the subjective test, and meanwhile the evaluation strategy is easy to implement for operators.

AB - For the popularity of delivering video service over HTTP Adaptive Streaming (HAS) in the mobile network, developing an automatic method to evaluate customers' quality of experience (QoE) for HAS video service in real time is highly desired for network operators and content providers. This paper proposes a novel QoE evaluation strategy for HAS video service based on the specific features of HAS and data-mining technology. Via capturing the media description files of HAS and the request information of clients, the QoE can be monitored in real time for operators. The evaluation algorithm for the proposed strategy is trained and tested based on the data sets collected from subjective test results. The test results suggest that the predicted Mean Opinion Score (pMOS) measured by our evaluation algorithm has high correlation with the Mean Opinion Score (MOS) measured by the subjective test, and meanwhile the evaluation strategy is easy to implement for operators.

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KW - MOS (Mean Opinion Score)

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KW - data mining

KW - pMOS (predicted Mean Opinion Score)

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ER -

A novel strategy to evaluate qoe for video service delivered over HTTP adaptive streaming

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Keywords

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