Information Fusion and Data Science

Mobile Data Mining and Applications

Authors: Jiang, H., Chen, Q., Zeng, Y., Li, D.

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  • Introduces a mobile data mining platform consistent with industry standards
  • Easily applicable to real-world scenarios
  • Includes hot topics such as mobile offloading and resource sharing
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eBook 83,29 €
price for Spain (gross)
  • ISBN 978-3-030-16503-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 135,19 €
price for Spain (gross)
  • Due: June 26, 2019
  • ISBN 978-3-030-16502-4
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities.

In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.

About the authors

Hao Jiang is currently a Professor with Wuhan University. He has authored over 60 papers journals and conference publications. His research interest includes mobile big data and mobile ad hoc networks.

Qimei Chen is an Associate Researcher with the School of Electronic Information at Wuhan University, China. Her current research interests are in the area of LTE-U, mobile edge computing, unmanned aerial vehicle, heterogeneous networks, and mmWave communications.

Yuanyuan Zeng is currently an Associate Professor at the School of Electronic Information, Wuhan University, China. She is also affiliated with the Collaborative Innovation Center for Geospatial Technology. She has published over 50 research papers in international journals and conference publications. Her research interests include mobile edge computing, network embedded systems, wireless sensor networks, and human-centric sensing. 

Deshi Li is a professor at Wuhan University and serves as a member of the Internet of Things Expert Committee and the Education Committee of Chinese Institute of Electronics.  Dr Li focuses his research in wireless communication, sensor networks, and SOC design 

Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook 83,29 €
price for Spain (gross)
  • ISBN 978-3-030-16503-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 135,19 €
price for Spain (gross)
  • Due: June 26, 2019
  • ISBN 978-3-030-16502-4
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Mobile Data Mining and Applications
Authors
Series Title
Information Fusion and Data Science
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-16503-1
DOI
10.1007/978-3-030-16503-1
Hardcover ISBN
978-3-030-16502-4
Series ISSN
2510-1528
Edition Number
1
Number of Pages
X, 227
Number of Illustrations
19 b/w illustrations, 77 illustrations in colour
Topics