Overview
- 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
Part of the book series: Information Fusion and Data Science (IFDS)
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Table of contents (6 chapters)
Keywords
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.
Authors and Affiliations
About the authors
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 memberof 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
Bibliographic Information
Book Title: Mobile Data Mining and Applications
Authors: Hao Jiang, Qimei Chen, Yuanyuan Zeng, Deshi Li
Series Title: Information Fusion and Data Science
DOI: https://doi.org/10.1007/978-3-030-16503-1
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-16502-4Published: 22 May 2019
eBook ISBN: 978-3-030-16503-1Published: 10 May 2019
Series ISSN: 2510-1528
Series E-ISSN: 2510-1536
Edition Number: 1
Number of Pages: X, 227
Number of Illustrations: 19 b/w illustrations, 77 illustrations in colour
Topics: Wireless and Mobile Communication, Data-driven Science, Modeling and Theory Building, Data Mining and Knowledge Discovery, Communications Engineering, Networks, Mobile Computing, Urban Geography / Urbanism (inc. megacities, cities, towns)