Big Data and Computational Intelligence in Networking
Editat de Yulei Wu, Fei Hu, Geyong Min, Albert Y. Zomayaen Limba Engleză Paperback – 30 iun 2020
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Specificații
ISBN-13: 9780367572440
ISBN-10: 0367572443
Pagini: 546
Dimensiuni: 156 x 234 x 30 mm
Greutate: 1.71 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
ISBN-10: 0367572443
Pagini: 546
Dimensiuni: 156 x 234 x 30 mm
Greutate: 1.71 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
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Cuprins
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
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
Notă biografică
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.
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.
Descriere
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.