Artificial intelligence for autonomous networks

405 Pages·2019·12.39 MB·English

by  Gilbert

Artificial Intelligence for
Autonomous Networks
Chapman & Hall/CRC
Artificial Intelligence and Robotics Series
Series Editor
Roman Yampolskiy
Contemporary Artificial Intelligence
Richard E. Neapolitan
The Virtual Mind
Designing the Logic to Approximate Human Thinking
Niklas Hageback
Intelligent Autonomy of UAVs
Advanced Missions and Future Use
Yasmina Bestaoui Sebbane
Artificial Intelligence
With an Introduction to Machine Learning, Second Edition
Richard E. Neapolitan, Xia Jiang
Artificial Intelligence and the Two Singularities
Calum Chace
Behavior Trees in Robotics and Artificial Intelligence
An Introduction
Michele Collendanchise, Petter Ögren
Artificial Intelligence Safety and Security
Roman V. Yampolskiy
Artificial Intelligence for Autonomous Networks
Mazin Gilbert
For more information about this series please visit:
https://www.crcpress.com/Chapman--HallCRC-Artificial-Intelligence-and-R obotics-
Series/book-series/ARTILRO
Artificial Intelligence for
Autonomous Networks
Edited by
Mazin Gilbert
CRC Press
Taylor & Francis Group
6000 Broken Sound Parkway NW, Suite 300
Boca Raton, FL 33487-2742
© 2019 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
No claim to original U.S. Government works
Printed on acid-free paper
International Standard Book Number-13: 978-0-8153-5531-1 (Hardback)
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made
to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all
materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all
material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been
obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future
reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in
any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, micro-
filming, and recording, or in any information storage or retrieval system, without written permission from the publishers.
For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.
copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-
8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that
have been granted a photocopy license by the CCC, a separate system of payment has been arranged.
Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identi-
fication and explanation without intent to infringe.
Visit the Taylor & Francis Web site at
http://www.taylorandfrancis.com
and the CRC Press Web site at
http://www.crcpress.com
Contents
Preface, vii
About the Editor, ix
Contributors, xi
CHAPTER 1 ◾ The Role of Artificial Intelligence for Network Automation
and Security 1
MAZIN GILBERT
CHAPTER 2 ◾ Machine Learning, Deep Learning, and Artificial Intelligence 25
MICHAEL LANZETTA
CHAPTER 3 ◾ The Shift to a Software-Defined Network 49
BRIAN FREEMAN AND PAUL BARTOLI
CHAPTER 4 ◾ Blockchain and Cryptography for Secure Information Sharing 69
MATT DUGAN AND WILEY WILKINS
CHAPTER 5 ◾ Building the Autonomous Networks of the Future 83
STEPHEN TERRILL AND MATTIAS LIDSTRÖM
CHAPTER 6 ◾ Role of Open Source, Standards, and Public Clouds
in Autonomous Networks 101
DAVID WARD AND CHRIS METZ
CHAPTER 7 ◾ Machine Learning, Containers, Cloud Natives, and
Microservices 145
EYAL FELSTAINE AND OFER HERMONI
CHAPTER 8 ◾ Artificial Intelligence Software and Hardware Platforms 165
RAJESH GADIYAR, TONG ZHANG, AND ANANTH SANKARANARAYANAN
v
vi ◾ Contents
CHAPTER 9 ◾ Artificial Intelligence for Network Operations 189
JENNIFER YATES AND ZIHUI GE
CHAPTER 10 ◾ Artificial Intelligence for Cybersecurity 231
ANESTIS KARASARIDIS, BRIAN REXROAD, AND PAT VELARDO
CHAPTER 11 ◾ Artificial Intelligence for Enterprise Networks 263
SANDEEP GUPTA, KATHLEEN MEIER-HELLSTERN, AND MICHAEL SATTERLEE
CHAPTER 12 ◾ Artificial Intelligence for 5G+, Edge Compute,
and Internet of Things 285
RITTWIK JANA, MARK AUSTIN, AND WENJIE ZHAO
CHAPTER 13 ◾ Artificial Intelligence for Infrastructure Monitoring
and Traffic Optimization 315
LAURIE BIGLER AND VIJAY GOPALAKRISHNAN
CHAPTER 14 ◾ Artificial Intelligence for Customer Experience and Care 345
JASON HUNT AND SUNIL DUBE
CHAPTER 15 ◾ New Artificial Intelligence Frontiers for Autonomous
Networks 361
ANIT LOHTIA AND CHRIS RICE
INDEX, 385
Preface
Last Monday morning, Lucy, my virtual assistant, woke me up.
While Lucy was monitoring my blood pressure and heartbeat in my sleep, she detected
abnormality and transmitted that information to my doctor. Lucy then went on to
summarize my calendar for the day, got my coffee ready, and charged my autonomous car.
Before leaving the house, I told Lucy to watch over my elderly mom and notify me when
she had taken her medicine. While in the car, I received a text message from my boss and
decided to hold a holographic meeting with him to discuss the matter. I arrived at work
and went straight to my office, and in the meantime, my car drove itself to the repair shop
for its annual check-up. During lunch, Lucy whispered in my ear to let me know that my
mom took her medicine and that she made an appointment with my doctor per his request.
Perhaps you have already guessed that this scenario is not real, but communication
has been progressing so rapidly over the past two decades that this amazing experience is
becoming more tangible. Underlying this scenario is a global communication network that
is able to connect people, robots, devices, and sensors in real time. This network may be one
of the most complex systems on the face of our planet and a monumental breakthrough in
the history of humanity. It has been exploding since the advent of smart phones, carrying
text, voice, video, and images, and soon fully 360 videos and holograms.
The network continues to undergo a massive transformation from hardware to software
and from being reactive to being proactive. In its first generation, also known as legacy, the
global communication network was monolithic and hardware/vendor-centric. Today, the
network is shifting to a second generation, a shift towards a software-centric network, in which
service functions are virtualized and run on commodity cloud hardware. Over the next
decade, the industry will be launching a third generation of this network transformation,
the autonomous network. The autonomous network is powered by data and adopts
artificial intelligence (AI). AI eats the network; in fact, it is an emerging reality that brings
significant opportunities and challenges ranging from algorithms and standardization to
real-time implementation and scale. Autonomous networks demonstrate a high degree
of intelligence and support the growing demands of 5G, Internet of Things (IoT), virtual
reality, and more. Those networks are self-healing and are capable of learning quickly
and defending themselves against all forms of cyber attacks. An autonomous network is a
living thing that you can talk to and interact with.
This book brings this autonomous network to reality by juxtaposing two unique
technologies and communities: Networking and AI. The first five chapters (Chapters 1
vii
viii ◾ Preface
through 5) review the technologies behind AI and software-defined network/network
function virtualization (SDN/NFV), highlighting the exciting opportunities to integrate
those two worlds into enabling secure autonomous networks. The next three chapters
(Chapters 6 through 8) will review the software side of the autonomous networks,
including the role of public cloud and open source, trends in containers and micro-services,
and evolving software and hardware platforms for supporting distributed and multi-
tenant AI platforms for autonomous networks. The following six chapters (Chapters 9
through 14) will dive into the application space and benefits of the autonomous network
for transforming network operation, cyber security, enterprise services, 5G and IoT,
infrastructure monitoring and traffic optimization, and customer experience and care.
Finally, Chapter 15 will outline new and exciting AI frontiers for autonomous networks.
I am sincerely thankful to the 31 incredible authors from 8 leading technology
companies for sharing their insights and expertise in this book. In particular, I would
like to acknowledge the contributions of Michael Lanzetta, Brian Freeman, Paul Bartoli,
Wiley Wilkins, Matt Dugan, Stephen Terrill, Mattias Lidström, David Ward, Chris Metz,
Eyal Felstaine, Ofer Hermoni, Rajesh Gadiyar, Ananth Sankaranarayanan, Tong Zhang, Jen
Yates, Zihui Ge, Pat Velardo, Brian Rexroad, Anestis Karasaridis, Sandeep Gupta, Kathleen
Meier-Hellstern, Michael Satterlee, Rittwik Jana, Mark Austin, Wenjie Zhao, Laurie Bigler,
Vijay Gopalakrishnan, Jason Hunt, Sunil Dube, Chris Rice, and Anit Lohtia.
I would also like to acknowledge the contributions of Natalie Gilbert, Swati Sharma,
Randi Cohen, and Umesh Desai in the editing of the book. Royalties of this book will be
for the Black Girls Code organization.
About the Editor
Dr. Mazin Gilbert is the vice president of Advanced Technology and Systems at AT&T
Labs. In this role, Mazin oversees advancements in networking and access systems,
machine learning and artificial intelligence, information systems and visualization, algo-
rithms and optimization, and scalable, reliable software platforms.
Mazin earned a bachelor’s degree and a doctoral degree, with first-class honors, in
electrical engineering from the University of Liverpool, Liverpool, England. He also
earned an MBA for Executives from the Wharton Business School of the University of
Pennsylvania, Philadelphia, Pennsylvania. He holds 175 U.S. patents in human–machine
communication and multimedia processing and has published over 100 technical papers.
He is the author of the book titled Artificial Neural Networks for Speech Analysis/Synthesis.
Mazin is the technical chair for the Linux Foundation Open Network Automation
Platform (ONAP), where his organization is actively contributing code and leading
multiple Technical Steering Committee projects. He is also the board chair for the Linux
Foundation Deep Learning Umbrella. Mazin and his team are co-founders of the open-
source projects on Acumos Deep Learning and Akraino EdgeStack that were recently
announced by the Linux Foundation. They are also contributors to OpenStack, Open
Network Function Virtualization (OPNFV), and OpenDaylight (ODL), among others.
With more than three decades of experience under his belt, Mazin has worked in the
industry at AT&T Labs and previously at Bell Labs, BBC, and British Telecom. He has also
worked in academia at Rutgers University, New Jersey, Princeton University, Princeton,
New Jersey, and University of Liverpool. Mazin is an IEEE Fellow and a winner of the
AT&T Science and Technology Award.
Outside of his technology career, Mazin is an entrepreneur owning six limited liability
companies specializing in commercial and residential real estate and the dental industry.
He also serves on a number of industrial boards, including the International Computer
Science Institute. In his free time, Mazin loves to spend time with his daughters and is an
avid runner.
ix