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Computing in Communication Networks: From Theory to Practice provides comprehensive details and practical implementation tactics on the novel concepts and enabling technologies at the core of the paradigm shift from store and forward (dumb) to compute and forward (intelligent) in future communication networks and systems. The book explains how to create virtualized large scale testbeds using well-established open source software, such as Mininet and Docker. It shows how and where to place disruptive techniques, such as machine learning, compressed sensing, or network coding in a newly built testbed. In addition, it presents a comprehensive overview of current standardization activities.
Specific chapters explore upcoming communication networks that support verticals in transportation, industry, construction, agriculture, health care and energy grids, underlying concepts, such as network slicing and mobile edge cloud, enabling technologies, such as SDN/NFV/ ICN, disruptive innovations, such as network coding, compressed sensing and machine learning, how to build a virtualized network infrastructure testbed on one’s own computer, and more.
- Provides a uniquely comprehensive overview on the individual building blocks that comprise the concept of computing in future networks
- Gives practical hands-on activities to bridge theory and implementation
- Includes software and examples that are not only employed throughout the book, but also hosted on a dedicated website
University researchers and R&D industry engineers in mobile and wireless communications engineering and computer networks, postgraduate students, undergraduate students
PART 1 FUTURE COMMUNICATION NETWORKS AND SYSTEMS
1. On the need of computing in future communication networks
2. Standardization activities for future communication networks
PART 2 CONCEPTS
3. Network slicing
4. Mobile edge cloud
5. Content distribution
PART 3 ENABLING TECHNOLOGIES
6. Software-defined networks
7. Network function virtualization
PART 4 INNOVATION TRACK
8. Machine learning
9. Network coding
10. Compressed sensing
PART 5 BUILDING THE TESTBED
11. Mininet: An insant virtual network on your computer
12. Docker: Containerize your application
13. ComNetsEmu: A lightweight emulator
PART 6 EXAMPLES
14. Realizing network slicing
15. Realizing mobile edge clouds
16. Machine learning for routing
17. Machine learning for flow compression
18. Machine learning for congestion control
19. Machine learning for object detection
20. Network coding for transport
21. Network coding for storage
22. In-network compressed sensing
23. Security for mobile edge cloud
PART 7 EXTENSIONS
24. Connecting to the outer world
25. Integrating time-sensitive networking
26. Integrating software-defined radios
PART 8 TOOLS
27. Networking tools
- No. of pages:
- © Academic Press 2020
- 21st May 2020
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Frank H. P. Fitzek is a Professor and head of the “Deutsche Telekom Chair of Communication Networks” at TU Dresden coordinating the 5G Lab Germany. He is the spokesman of the DFG Cluster of Excellence “Center for Tactile Internet” (CeTI). He received his diploma (Dipl.-Ing.) degree in electrical engineering from the University of Technology – Rheinisch-Westfälische Technische Hochschule (RWTH) – Aachen, Germany, in 1997 and his Ph.D. (Dr.-Ing.) in Electrical Engineering from the Technical University Berlin, Germany in 2002 and became Adjunct Professor at the University of Ferrara, Italy in the same year. In 2003 he joined Aalborg University as Professor .
Professor and head of the “Deutsche Telekom Chair of Communication Networks”, TU Dresden, 5G Lab, Germany
Fabrizio Granelli is Associate Professor at the Dept. of Information Engineering and Computer Science (DISI) – University of Trento (Italy), IEEE ComSoc Director for Educational Services (2018-19) and Chair of Joint IEEE VTS/ComSoc Italian Chapter. He is Research Associate Professor at the University of New Mexico, NM, USA. He received the M.Sc. and Ph.D. degrees from University of Genoa, Italy, in 1997 and 2001. He was visiting professor at the State University of Campinas (Brasil) and at the University of Tokyo (Japan), and IEEE ComSoc Distinguished Lecturer in 2012-15. He is Associate Editor in Chief of IEEE Communications Surveys and Tutorials.
Associate Professor, DISI - University of Trento, Italy
Patrick Seeling is a Professor in the Department of Computer Science at Central Michigan University, USA. He received his diploma (Dipl.-Ing.) degree in Industrial Engineering and Management from the Technical University Berlin, Germany, in 2002 and his his Ph.D. in Electrical Engineering from Arizona State University (ASU), USA, in 2005. He was an Associated Faculty at ASU until 2008 and an Assistant Professor at the University of Wisconsin-Stevens Point until 2011. In 2011, he joined Central Michigan University as Assistant Professor, where he became a tenured Associate Professor in 2015 and a Full Professor in 2018.
Professor, Department of Computer Science, Michigan University, USA
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