

Beschreibung
This book provides a comprehensive picture of mobile big data starting from data sources to mobile data driven applications. Mobile Big Data comprises two main components: an overview of mobile big data, and the case studies based on real-world data recently ...This book provides a comprehensive picture of mobile big data starting from data sources to mobile data driven applications. Mobile Big Data comprises two main components: an overview of mobile big data, and the case studies based on real-world data recently collected by one of the largest mobile network carriers in China.
In the first component, four areas of mobile big data life cycle are surveyed: data source and collection, transmission, computing platform and applications. In the second component, two case studies are provided, based on the signaling data collected in the cellular core network in terms of subscriber privacy evaluation and demand forecasting for network management. These cases respectively give a vivid demonstration of what mobile big data looks like, and how it can be analyzed and mined to generate useful and meaningful information and knowledge.
This book targets researchers, practitioners and professors relevant to this field. Advanced-level students studying computer science and electrical engineering will also be interested in this book as supplemental reading.
Provides a comprehensive overview of mobile big data life cycle, including data source & collection, transmission, computing platform, and data-driven applications Includes two case studies in detail with the real-world collected mobile big data to vividly demonstrate the mobile big data analysis and mining in terms of subscriber privacy and demand forecasting Surveys the supporting infrastructure on communications and networks for mobile big data transmission
Autorentext
Dr. Xiang Cheng (S'05-M'10-SM'13-F'22) received the Ph.D. degree jointly from Heriot-Watt University and the University of Edinburgh, Edinburgh, U.K., in 2009. He is currently a Boya Distinguished Professor of Peking University. His general research interests are in areas of channel modeling, wireless communications, and data analytics, subject on which he has published more than 280 journal and conference papers, 9 books, and holds 17 patents. Prof. Cheng is a Distinguished Young Investigator of China Frontiers of Engineering, a recipient of the IEEE Asia Pacific Outstanding Young Researcher Award in 2015, a Distinguished Lecturer of IEEE Vehicular Technology Society, and a Highly Cited Chinese Researcher in 2020. He was a co-recipient of the 2016 IEEE JSAC Best Paper Award: Leonard G. Abraham Prize, and IET Communications Best Paper Award: Premium Award. He has also received the Best Paper Awards at IEEE ITST'12, ICCC'13, ITSC'14, ICC'16, ICNC'17, GLOBECOM'18, ICCS'18, andICC'19. He has served as the symposium lead chair, co-chair, and member of the Technical Program Committee for several international conferences. He is currently a Subject Editor of IET Communications and an Associate Editor of the IEEE Transactions on Wireless Communications, IEEE Transactions on Intelligent Transportation Systems, IEEE Wireless Communications Letters, and the Journal of Communications and Information Networks. Shijian Gao (S'20) received the B.Sc. and M.Sc. degrees from Nankai University and Peking University in 2014 and 2017, respectively, both in electrical engineering. He is currently working towards the Ph.D. degree with the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis. His research interests are in the areas of wireless communications and related fields. Dr. Liuqing Yang (S'02-M'04-SM'06-F'15) received the Ph.D. degree in electrical and computer engineering from the Universityof Minnesota, Minneapolis, MN, USA, in 2004. She is currently a Professor with Hong Kong University of Science and Technology (Guangzhou). Her general interests are in signal processing with applications to communications, networking, and power systems-subjects on which she has published more than 370 journal and conference papers, four book chapters, and five books. Dr. Yang was a recipient of the ONR Young Investigator Program Award in 2007, and the NSF Faculty Early Career Development (CAREER) Award in 2009, the Best Paper Award at the IEEE ICUWB'06, ICCC'13, ITSC'14, Globecom'14, ICC'16, WCSP'16, Globecom'18, ICCS'18, and ICC'19. She is the Editor-in-Chief for IET Communications, Senior Editor for IEEE Transactions on Signal Processing, and the Executive Editorial Committee member for IEEE Transactions on Wireless Communications. She has served as an Associate/Senior Editor for IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions onSignal Processing, the IEEE Transactions on Intelligent Transportation Systems, IEEE Intelligent Systems, and PHYCOM: Physical Communication, and as the program chair and the track/symposium or TPC chair for many conferences.
Klappentext
This book provides a comprehensive picture of mobile big data starting from data sources to mobile data driven applications. Mobile Big Data comprises two main components: an overview of mobile big data, and the case studies based on real-world data recently collected by one of the largest mobile network carriers in China. In the first component, four areas of mobile big data life cycle are surveyed: data source and collection, transmission, computing platform and applications. In the second component, two case studies are provided, based on the signaling data collected in the cellular core network in terms of subscriber privacy evaluation and demand forecasting for network management. These cases respectively give a vivid demonstration of what mobile big data looks like, and how it can be analyzed and mined to generate useful and meaningful information and knowledge. This book targets researchers, practitioners and professors relevant to this field. Advanced-level students studying computer science and electrical engineering will also be interested in this book as supplemental reading.
Inhalt
1 Mobile Big Data.- 2 Source and Collection.- 3 Transmission.- 4 Computing.- 5 Applications.- 6 Case Study: Demand Forecasting for Predictive Network Managements.- 7 Case Study: User Identification for Mobile Privacy.
