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QoE-Based Performance Evaluation for Adaptive Media Playout Systems

DOI: 10.1155/2013/152359

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To improve the playout quality of video streaming services, several adaptive media playout (AMP) mechanisms were proposed in literature. However, all performance evaluations and comparisons for AMPs were made in terms of quality of service (QoS) metrics. As one knows, there may exist a trade-off between QoS metrics, such as buffer underflow and overflow performance. Thus, it is not sufficient to only evaluate the performance of AMPs in terms of QoS metrics. In this paper, we will evaluate and compare the performance of several AMPs from the aspect of quality of experience (QoE). Numerical results will show that some existing AMP systems do not perform better than the nonadaptive playout system from the point of view of overall QoE. 1. Introduction Recently, multimedia streaming applications such as IPTV [1] have been increasing rapidly due to the significant growth of bandwidth in access networks, such as xDSL, FTTH, 3G/4G, and WiMAX. However, due to the random delay/jitter encountered in Internet, at the client side the video playout interruption, block distortions, and nonpredictive preroll time may occur during a playout session. To counteract the effects of network jitter on the quality of video streaming, adaptive media playout (AMP) techniques, which can control the media playout rate dynamically, have emerged [2–10]. Some AMP schemes, such as [2–7], adjust the media playout rate dynamically according to the buffer fullness. Another AMP based on buffer variation rather than buffer fullness was proposed in [8]. The other content-aware AMPs that take into account the content of a video sequence and motion characteristics of different scenes were presented in [9, 10]. The content-aware AMP only slows down the low-motion scenes such that the perceived effect is lower. The quality of service (QoS) refers to several related aspects of telephony and computer networks that allow the transport of traffic with special requirements. QoS metrics belong to quantitative metrics that can be measured objectively by using network equipment. Therefore, they are usually called objective QoS metrics. Several objective QoS metrics, such as underflow probability, overflow probability, variance of distortion of playout (VDoP) [3, 7], initial playout delay, playout curve, and mean playout rate have been used for evaluating the performance of AMP mechanisms. Detailed definitions of most of these objective metrics can be found in [7]. Several works had shown that there may exist a trade-off among these metrics mentioned above [4, 7]. For example, there exists a trade-off


[1]  Y. Xiao, X. Du, J. Zhang, F. Hu, and S. Guizani, “Internet protocol television (IPTV): the killer application for the next-generation internet,” IEEE Communications Magazine, vol. 45, no. 11, pp. 126–134, 2007.
[2]  M. C. Yuang, S. T. Liang, and Y. G. Chen, “Dynamic video playout smoothing method for multimedia applications,” Multimedia Tools and Applications, vol. 6, no. 1, pp. 47–60, 1998.
[3]  N. Laoutaris and I. Stavrakakis, “Adaptive playout strategies for packet video receivers with finite buffer capacity,” in Proceedings of International Conference on Communications (ICC '01), pp. 969–973, June 2001.
[4]  M. Kalman, E. Steinbach, and B. Girod, “Adaptive media playout for low-delay video streaming over error-prone channels,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 6, pp. 841–851, 2004.
[5]  Y. Li, A. Markopoulou, N. Bambos, and J. Apostolopoulos, “Joint power-playout control for media streaming over wireless links,” IEEE Transactions on Multimedia, vol. 8, no. 4, pp. 830–843, 2006.
[6]  S. Deshpande, “Underflow prevention for AV streaming media under varying channel conditions,” in Multimedia on Mobile Devices 2007, vol. 6507 of Proceedings of the SPIE, January 2007.
[7]  M. Li, T. W. Lin, and S. H. Cheng, “Arrival process-controlled adaptive media playout with multiple thresholds for video streaming,” Multimedia Systems, vol. 18, no. 5, pp. 391–407, 2012.
[8]  Y. F. Su, Y. H. Yang, M. T. Lu, and H. H. Chen, “Smooth control of adaptive media playout for video streaming,” IEEE Transactions on Multimedia, vol. 11, no. 7, pp. 1331–1339, 2009.
[9]  H. C. Chuang, C. Huang, and T. Chiang, “Content-aware adaptive media playout controls for wireless video streaming,” IEEE Transactions on Multimedia, vol. 9, no. 6, pp. 1273–1283, 2007.
[10]  Y. Li, A. Markopoulou, J. Apostolopoulos, and N. Bambos, “Content-aware playout and packet scheduling for video streaming over wireless links,” IEEE Transactions on Multimedia, vol. 10, no. 5, pp. 885–895, 2008.
[11]  A. Takahashi, D. Hands, and V. Barriac, “Standardization activities in the ITU for a QoE assessment of IPTV,” IEEE Communications Magazine, vol. 46, no. 2, pp. 78–84, 2008.
[12]  B. Wang, X. Wen, S. Yong, and Z. Wei, “A new approach measuring users' QoE in the IPTV,” in Proceedings of Pacific-Asia Conference on Circuits, Communications and System (PACCS '09), pp. 453–456, May 2009.
[13]  K. Piamrat, C. Viho, A. Ksentini, and J. M. Bonnin, “Quality of experience measurements for video streaming over wireless networks,” in Proceedings of the 6th International Conference on Information Technology: New Generations (ITNG '09), pp. 1184–1189, April 2009.
[14]  A. Khan, L. Sun, and E. Ifeachor, “QoE prediction model and its application in video quality adaptation over UMTS networks,” IEEE Transactions on Multimedia, vol. 14, no. 2, pp. 431–442, 2012.
[15]  M. H. Pinson and S. Wolf, “A new standardized method for objectively measuring video quality,” IEEE Transactions on Broadcasting, vol. 50, no. 3, pp. 312–322, 2004.
[16]  Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity,” IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, 2004.
[17]  H. J. Kim, D. H. Lee, J. M. Lee, K. H. Lee, W. Lyu, and S. G. Choi, “The QoE evaluation method through the QoS-QoE correlation model,” in Proceedings of the 4th International Conference on Networked Computing and Advanced Information Management (NCM '08), pp. 719–725, September 2008.
[18]  H. J. Kim and S. G. Choi, “A study on a QoS/QoE correlation model for QoE evaluation on IPTV service,” in Proceedings of the 12th International Conference on Advanced Communication Technology: ICT for Green Growth and Sustainable Development (ICACT '10), pp. 1377–1382, February 2010.
[19]  ITU-T Rec., “P. 800, Mean Opinion Score (MOS) Terminology,” March 2003.
[20]  M. Li and C.-Y. Lee, “A cost-effective and real-time QoE evaluation method for multimedia streaming Services,” Telecommunication Systems, Special Issue on Innovations in Emerging Multimedia Communication Systems. In press.
[21]  The Network Simulator (NS2),


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