Big Data and Computational Intelligence in Networking

This book presents state-of-the-art solutions to the theoretical and practical challenges stemming from the leverage of big data and its computational intelligence in supporting smart network operation, management, and optimization. In particular, the technical focus covers the comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for network big data, and emerging applications of network big data for computational intelligence.

Dr. Yulei Wu is a Lecturer in Computer Science at the University of Exeter. He received his Ph.D. degree in Computing and Mathematics and B.Sc. (First Class Hons) degree in Computer Science from the University of Bradford, UK, in 2010 and 2006, respectively. His main research focuses on Big Data, Future Internet Architecture, Wireless Networks and Mobile Computing, Cloud Computing, and Performance Modelling and Analysis. Before joining the University of Exeter, he was working as an Associate Professor in the Chinese Academy of Sciences (CAS). During his stay in CAS, he mainly worked in the field of Internet Architecture and Big Data. He was the Principal Investigator of a National Natural Science Foundation of China (NFSC) project on Content Delivery Networks, and was the Co-Investigator of a National High-tech R&D ("863") project on Virtual Router, a National Key Technologies R&D project on IPv6, and a CAS Strategic Priority Research project on Future Internet Research Testbed.
 

Dr. Fei Hu is currently a professor in the Department of Electrical and Computer Engineering at the University of Alabama (main campus), Tuscaloosa, Alabama, USA. He obtained his Ph.D. degrees at Tongji University (Shanghai, China) in the field of Signal Processing (in 1999), and at Clarkson University (New York, USA) in the field of Electrical and Computer Engineering (in 2002). He has published over 200 journal/conference papers, books, and book chapters. Dr. Hu's research has been supported by U.S. National Science Foundation (NSF), U.S. Department of Defense (DoD), Cisco, Sprint, and other sources. He has chaired a few international conferences. His research interests are 3S - Security, Signals, Sensors: (1) Security: This is about how to overcome different cyber attacks in a complex wireless or wired network. Recently he focuses on cyber-physical system security and medical security issues. (2) Signals: This mainly refers to intelligent signal processing, that is, using machine learning algorithms to process sensing signals in a smart way in order to extract patterns (i.e., achieve pattern recognition). (3) Sensors: This includes micro-sensor design and wireless sensor networking issues.