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Estimation of in‐service quality of experience for peer‐to‐peer live video streaming systems using a user‐centric and context‐aware approach based on Bayesian networks
Author(s) -
Mian Ahmad Umair,
Hu Zheng,
Tian Hui
Publication year - 2013
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.2641
Subject(s) - computer science , quality of experience , provisioning , context (archaeology) , peer to peer , bayesian network , service (business) , quality of service , computer network , distributed computing , multimedia , real time computing , machine learning , paleontology , economy , economics , biology
In this paper, a modified and improved quality of experience (QoE) estimation approach has been presented on the basis of the user‐behavior modelling and context‐aware modelling. We have implemented this proposed approach for peer‐to‐peer live video streaming systems because of the dynamically adaptive and distributed nature of these systems. The problem of estimating QoE is formulated as a Bayesian network model using user‐behavior and context‐related variables as nodes. The relationship between these nodes are established to find out estimated QoE, which is based on the user‐behavior data and context data, and dynamically adapt to any change in their values. This relationship is further explored to provide the basis for more user‐centric, context‐aware and dynamically adaptive services and network systems as this in‐service QoE is important for network optimization and service provisioning. Copyright © 2013 John Wiley & Sons, Ltd.