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International Journal of Digital Multimedia Broadcasting
Volume 2012 (2012), Article ID 904072, 13 pages
Research Article

Multi-Resolution Multimedia QoE Models for IPTV Applications

1Ohio Supercomputer Center/OARnet, The Ohio State University, Columbus, OH 43210, USA
2Huawei Technologies, Shenzhen 518129, China

Received 2 April 2011; Accepted 27 September 2011

Academic Editor: Thomas Magedanz

Copyright © 2012 Prasad Calyam et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Internet television (IPTV) is rapidly gaining popularity and is being widely deployed in content delivery networks on the Internet. In order to proactively deliver optimum user quality of experience (QoE) for IPTV, service providers need to identify network bottlenecks in real time. In this paper, we develop psycho-acoustic-visual models that can predict user QoE of multimedia applications in real time based on online network status measurements. Our models are neural network based and cater to multi-resolution IPTV applications that include QCIF, QVGA, SD, and HD resolutions encoded using popular audio and video codec combinations. On the network side, our models account for jitter and loss levels, as well as router queuing disciplines: packet-ordered and time-ordered FIFO. We evaluate the performance of our multi-resolution multimedia QoE models in terms of prediction characteristics, accuracy, speed, and consistency. Our evaluation results demonstrate that the models are pertinent for real-time QoE monitoring and resource adaptation in IPTV content delivery networks.