TY - GEN
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
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/11/24
Y1 - 2014/11/24
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.
KW - HTTP Adaptive Streaming (HAS)
KW - MOS (Mean Opinion Score)
KW - Quality of experience (QoE)
KW - data mining
KW - pMOS (predicted Mean Opinion Score)
UR - http://www.scopus.com/inward/record.url?scp=84919459622&partnerID=8YFLogxK
U2 - 10.1109/VTCFall.2014.6965834
DO - 10.1109/VTCFall.2014.6965834
M3 - Conference contribution
AN - SCOPUS:84919459622
T3 - IEEE Vehicular Technology Conference
BT - 2014 IEEE 80th Vehicular Technology Conference, VTC2014-Fall, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 80th IEEE Vehicular Technology Conference, VTC 2014-Fall
Y2 - 14 September 2014 through 17 September 2014
ER -