Performance Evaluation of a Decision-Theoretic Approach for Quality of Experience Measurement in Mobile and Pervasive Computing Scenarios

Provided by: Institute of Electrical & Electronic Engineers
Topic: Mobility
Format: PDF
Measuring 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, the authors 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.

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