A decision-theoretic approach for quality-of-experience measurement and prediction

Authors:
Karan Mitra;Christer Ahlund;Arkady Zaslavsky
Affiliations:
Fac. of Inf. Technol., Monash Univ., Melbourne, VIC, Australia;Lulea Univ. of Technol., Lulea, Sweden;Fac. of Inf. Technol., Monash Univ., Melbourne, VIC, Australia
Venue:
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
Year:
2011

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Dynamic bayesian networks for sequential quality of experience modelling and measurement

NEW2AN'11/ruSMART'11 Proceedings of the 11th international conference and 4th international conference on Smart spaces and next generation wired/wireless networking

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Abstract

This paper presents a pioneering context-aware approach for quality of experience (QoE) measurement and prediction. The proposed approach incorporates an intuitive context-aware framework and decision theory. It is capable of incorporating several QoE related classes and context information to correctly measure and predict the overall QoE on a single scale. Our approach can be used in measuring and predicting QoE in both lab and living-lab settings based on user, device and network related context parameters. The predicted QoE can be beneficial for network operators to minimize network churn and can help application developers to build smart user-centric applications. We perform extensive experimentation and the results validate our approach.