Computing in Communication Networks: From Theory to Practice
Editat de Frank H. P. Fitzek, Fabrizio Granelli, Patrick Seelingen Limba Engleză Paperback – 20 mai 2020
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
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Specificații
ISBN-13: 9780128204887
ISBN-10: 0128204885
Pagini: 522
Ilustrații: Approx. 100 illustrations
Dimensiuni: 191 x 235 mm
Greutate: 0.89 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128204885
Pagini: 522
Ilustrații: Approx. 100 illustrations
Dimensiuni: 191 x 235 mm
Greutate: 0.89 kg
Editura: ELSEVIER SCIENCE
Public țintă
University researchers, R&D industry engineers in mobile and wireless communications engineering and computer networksCuprins
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
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