Mobile Data Mining and Applications
Liburu elektroniko honi buruz
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.
Egileari buruz
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
