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Performance evaluation of a decision-theoretic approach for quality of experience measurement in mobile and pervasive computing scenarios
conference contribution
posted on 2023-01-27, 04:41 authored by K Mitra, C Åhlund, Arkady ZaslavskyArkady ZaslavskyMeasuring and predicting users quality of experience (QoE) in dynamic network conditions is a challenging task. This paper presents results related to a decision-theoretic methodology incorporating Bayesian networks (BNs) and utility theory for quality of experience (QoE) measurement and prediction in mobile computing scenarios. In particular, we show how both generative and discriminative BNs can be used to measure and predict users QoE accurately for voice applications under several wireless network conditions such as wireless signal fading, vertical handoffs, wireless network congestion and normal hotspot traffic. Through extensive simulation studies and results analysis, we show that our proposed methodology can achieve an average accuracy of 98.70% using three different types of Bayesian network. © 2012 IEEE.
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2418 - 2423Publisher DOI
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1525-3511ISBN-13
9781467304375Publication classification
E1.1 Full written paper - refereedTitle of proceedings
IEEE Wireless Communications and Networking Conference, WCNCUsage metrics
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