Table of contents
About this book
This SpringerBrief presents research results on QoE management schemes for mobile services, including user services, and resource allocation. Along with a review of the research literature, it offers a data-driven architecture for personalized QoE management in wireless networks. The primary focus is on introducing efficient personalized character extraction mechanisms, e.g., context-aware Bayesian graph model, and cooperative QoE management mechanisms. Moreover, in order to demonstrate in the effectiveness of the QoE model, a QoE measurement platform is described and its collected data examined. The brief concludes with a discussion of future research directions.
The example mechanisms and the data-driven architecture provide useful insights into the designs of QoE management, and motivate a new line of thinking for users' satisfaction in future wireless networks.
Wireless networks QoE management Data-driven architecture User-service preference Resource allocation Personalized character extraction 5G
- DOI https://doi.org/10.1007/978-3-319-42454-5
- Copyright Information The Author(s) 2017
- Publisher Name Springer, Cham
- eBook Packages Engineering Engineering (R0)
- Print ISBN 978-3-319-42452-1
- Online ISBN 978-3-319-42454-5
- Series Print ISSN 2191-8112
- Series Online ISSN 2191-8120
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