QoE Management in Wireless Networks (Paperback, 1st ed. 2017)

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

SpringerBriefs in Electrical and Computer Engineering

Release date

August 2016

Availability

Expected to ship within 10 - 15 working days

First published

2017

Authors

, ,

Dimensions

235 x 155 x 4mm (L x W x T)

Format

Paperback

Pages

60

Edition

1st ed. 2017

ISBN-13

978-3-319-42452-1

Barcode

9783319424521

Categories

LSN

3-319-42452-1



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