Table of Contents

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

About the Author

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.