Computing in Communication Networks

From Theory to Practice

Frank H. P. Fitzek, Fabrizio Granelli, Patrick Seeling, Frank Fitzek

• Publisher: Academic Press
• Year: 2020
• Print ISBN:
  9780128204887
• eBook ISBN:
  9780128209042
• Topic: Technology & Engineering
• Subtopic: Computer Networking
• Index: Technology & Engineering

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

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• List of contributors
• About the editors
• Preface from the editors
• Acknowledgments
• Acronyms
• Part 1: Future communication networks and systems
• Introduction
• Chapter 1: On the need of computing in future communication networks
• Chapter 2: Standardization activities for future communication networks
• Part 2: Concepts
• Introduction
• Chapter 3: Network slicing
• Chapter 4: Mobile edge cloud
• Chapter 5: Content distribution
• Part 3: Enabling technologies
• Introduction
• Chapter 6: Software-defined networks
• Chapter 7: Network function virtualization
• Part 4: Innovation track
• Introduction
• Chapter 8: Machine learning
• Chapter 9: Network coding
• Chapter 10: Compressed sensing
• Part 5: Building the testbed
• Introduction
• Chapter 11: Mininet: an instant virtual network on your computer
• Chapter 12: Docker: containerize your application
• Chapter 13: ComNetsEmu: a lightweight emulator
• Part 6: Examples
• Introduction
• Chapter 14: Realizing network slicing
• Chapter 15: Realizing mobile edge clouds
• Chapter 16: Machine learning for routing
• Chapter 17: Machine learning for flow compression
• Chapter 18: Machine learning for congestion control
• Chapter 19: Machine learning for object detection
• Chapter 20: Network coding for transport
• Chapter 21: Network coding for storage
• Chapter 22: In-network compressed sensing
• Chapter 23: Security for mobile edge cloud
• Part 7: Extensions
• Introduction
• Chapter 24: Connecting to the outer world
• Chapter 25: Integrating time-sensitive networking
• Chapter 26: Integrating software-defined radios
• Part 8: Tools
• Introduction
• Chapter 27: Networking tools
• Bibliography
• Index