Multi-Resolution Multimedia QoE Models for IPTV Applications. (12th January 2012)

• Record Type: Journal Article
• Authors: Calyam, Prasad; Chandrasekaran, Prashanth; Trueb, Gregg; Howes, Nathan; Ramnath, Rajiv; Yu, Delei; Liu, Ying; Xiong, Lixia; Yang, Daoyan
• Other Names: Magedanz Thomas Academic Editor.
• Is Part Of: International journal of digital multimedia broadcasting. Volume 2012(2012)
• Publication Date: 2012-01-12
• Subjects: Multimedia communications -- Periodicals; Digital audio broadcasting -- Periodicals; Mobile communication systems -- Periodicals; Digital audio broadcasting; Mobile communication systems; Multimedia communications; Periodicals; 621.382
• DOI: 10.1155/2012/904072
• Languages: English
• ISSNs: 1687-7578

Abstract

Abstract : 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.