Quality of Experience Models for Multimedia Streaming

Quality of Experience Models for Multimedia Streaming

Vlado Menkovski (Eindhoven University of Technology, The Netherlands), Georgios Exarchakos (Eindhoven University of Technology, The Netherlands), Antonio Liotta (Eindhoven University of Technology, The Netherlands) and Antonio Cuadra Sánchez (Telefonica R&D, Spain)
DOI: 10.4018/978-1-4666-0119-2.ch008
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Abstract

Understanding how quality is perceived by viewers of multimedia streaming services is essential for efficient management of those services. Quality of Experience (QoE) is a subjective metric that quantifies the perceived quality, which is crucial in the process of optimizing tradeoff between quality and resources. However, accurate estimation of QoE often entails cumbersome studies that are long and expensive to execute. In this regard, the authors present a QoE estimation methodology for developing Machine Learning prediction models based on initial restricted-size subjective tests. Experimental results on subjective data from streaming multimedia tests show that the Machine Learning models outperform other statistical methods achieving accuracy greater than 90%. These models are suitable for real-time use due to their small computational complexity. Even though they have high accuracy, these models are static and cannot adapt to environmental change. To maintain the accuracy of the prediction models, the authors have adopted Online Learning techniques that update the models on data from subjective viewer feedback. This method provides accurate and adaptive QoE prediction models that are an indispensible component of a QoE-aware management service.
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Qoe Measurement Methods

Perception of quality in multimedia streaming is getting more attention with the proliferation of high quality multimedia technologies. The reason for this is twofold; on the one hand, user’s expectation of quality has increased and, on the other, managing the larger demand on the network resources has become a more pressing matter. There are many aspects and dimensions of perceived quality but the focus of this paper, regarding the multimedia services, is the QoE as a comprehensive quality metric.

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