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.

PART I: BASICS OF NETWORKED BIG DATA 1. A Survey of Big Data and Computational Intelligence In Networking Yujia Zhu, Yulei Wu, Geyong Min, Albert Zomaya, and Fei Hu 2. Some Mathematical Properties of Networks for Big Data Marcello Trovati 3. Big Geospatial Data and the Geospatial Semantic Web: Current State and Future Opportunities Chuanrong Zhang, Tian Zhao, and Weidong Li 4. Big Data over Wireless Networks (WiBi) Immanuel Manohar and Fei Hu PART II: NETWORK ARCHITECTURE FOR BIG DATA TRANSMISSIONS 5. Efficient Big Data Transfer Using Bandwidth Reservation Service In High-Performance Networks Liudong Zuo and Michelle Mengxia Zhu 6. A Dynamic Cloud Computing Architecture for Cloud-Assisted Internet of Things in the Era of Big Data Mehdi Bahrami and Mukesh Singhal 7. Bicriteria Task Scheduling and Resource Allocation for Streaming Big Data Processing in Geo-Distributed Clouds Deze Zeng, Chengyu Hu, Guo Ren, and Lin Gu PART III: ANALYSIS AND PROCESSING OF NETWORKED BIG DATA 8. The ADMM and Its Application to Network Big Data Nan Lin and Liqun Yu 9. Hyperbolic Big Data Analytics for Dynamic Network Management and Optimization Vasileios Karyotis and Eleni Stai 10. Predictive Analytics for Network Big Data Using Knowledge-Based Reasoning for Smart Retrieval of Data, Information, Knowledge, and Wisdom (DIKW) Aziyati Yusoff, Norashidah Md. Din, Salman Yussof, Assad Abbas, and Samee U. Khan 11. Recommendation Systems Joonseok Lee 12. Coordinate Gradient Descent Methods Ion Necoara 13. Data Locality and Dependency for MapReduce Xiaoqiang Ma, Xiaoyi Fan, and Jiangchuan Liu 14. Distributed Machine Learning for Network Big Data Seunghak Lee 15. Big Data Security: Toward a Hashed Big Graph Yu Lu and Fei Hu PART IV: EMERGING APPLICATIONS OF NETWORKED BIG DATA 16. Mobile Augmented Reality to Enable Intelligent Mall Shopping By Network Data Vincent W. Zheng and Hong Cao 17. Toward Practical Anomaly Detection in Network Big Data Chengqiang Huang, Yulei Wu, Zuo Yuan, and Geyong Min 18. Emerging Applications of Spatial Network Big Data In Transportation Reem Y. Ali, Venkata M.V. Gunturi, Zhe Jiang, and Shashi Shekhar 19. On Emerging Use Cases and Techniques in Large Networked Data in Biomedical and Social Media Domain Vishrawas Gopalakrishnan and Aidong Zhang 20. Big Data Analysis for Smart Manufacturing Z. Y. Liu and Y. B. Guo

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.