Metaverse Communication and Computing Networks E-Book
107,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Metaverse Communication and Computing Networks Understand the future of the Internet with this wide-ranging analysis "Metaverse" is the term for applications that allow users to assume digital avatars to interact with other humans and software functions in a three-dimensional virtual space. These applications and the spaces they create constitute an exciting and challenging new frontier in digital communication. Surmounting the technological and conceptual barriers to creating the Metaverse will require researchers and engineers familiar with its underlying theories and a wide range of technologies and techniques. Metaverse Communication and Computing Networks provides a comprehensive treatment of Metaverse theory and the technologies that can be brought to bear on this new pursuit. It begins by describing the Metaverse's underlying architecture and infrastructure, physical and digital, before addressing how existing technologies are being adapted to its use. It concludes with an overview of the challenges facing the Metaverse. The result is a thorough introduction to a subject that may define the future of the internet. Metaverse Communication and Computing Networks readers will also find: * Detailed treatment of technologies, including artificial intelligence, Virtual Reality, Extended Reality, and more * Analysis of issues including data security, ethics, privacy, and social impact * A real-world prototype for Metaverse applications Metaverse Communication and Computing Networks is a must-own for researchers and engineers looking to understand this growing area of technology, and entrepreneurs interested in establishing Metaverse businesses.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 629
Veröffentlichungsjahr: 2023
Ähnliche
Table of Contents
Cover
Table of Contents
Title Page
Copyright
Dedication
Editors' Biography
List of Contributors
Preface
Acknowledgments
Introduction
1 Metaverse: An Introduction
1.1 Introduction
1.2 The Metaverse: Fantasy, Text, 3D Worlds
1.3 The Rise of Edge Computing
1.4 Universality, Interoperability, and Openness
1.5 Steps Toward Mobile User Interaction Within the Metaverse
1.6 Bringing Users' Profiles and Assets on the Metaverse
1.7 Conclusions and Future Research Directions
Bibliography
2 Potential Applications and Benefits of Metaverse
2.1 Metaverse Applications for Entertainment
2.2 Virtual Office in Metaverse
2.3 Education
2.4 Metaverse for Healthcare Services
2.5 Metaverse for Autonomous Vehicles
2.6 Metaverse for Virtual Travelling
2.7 Conclusions and Future Research Directions
Bibliography
3 Metaverse Prototype: A Case Study
3.1 Overview
3.2 Newbie at CUHKSZ
3.3 CUHKSZ Metaverse
3.4 Conclusions and Future Research Directions
Acknowledgement
Bibliography
4 Wireless Technologies for the Metaverse
4.1 Introduction
4.2 XR over NR: Standardization in 3GPP
4.3 Case Study: Location‐Dependent AR Services in the Wireless Edge‐Enabled Metaverse
4.4 Conclusions and Future Research Directions
Acknowledgment
Bibliography
5 AI and Computer Vision Technologies for Metaverse
5.1 Introduction
5.2 AI for the Metaverse
5.3 Computer Vision for the Metaverse
5.4 Conclusions and Future Research Directions
Bibliography
6 Virtual/Augmented/Mixed Reality Technologies for Enabling Metaverse
6.1 Introduction
6.2 Virtual Reality
6.3 Augmented Reality
6.4 Mixed Reality
6.5 Conclusions and Future Research Directions
Acknowledgments
Bibliography
7 Blockchain for the Metaverse: State‐of‐the‐Art and Applications
7.1 Introduction
7.2 Background
7.3 Use Cases of Blockchain for the Metaverse
7.4 Projects
7.5 Conclusions and Future Research Directions
Bibliography
8 Edge Computing Technologies for Metaverse
8.1 An Overview of Edge‐enabled Metaverse
8.2 Opportunities and Challenges in the Edge‐enabled Metaverse
8.3 Edge‐Enabled Metaverse: Release the Ubiquitous Computing and Intelligence at the Edge
8.4 Conclusions and Future Research Directions
Bibliography
9 Security Issues in Metaverse
9.1 Overview of Security and Privacy Threats in Metaverse
9.2 Threats and Countermeasures to Authentication and Access Control in Metaverse
9.3 Threats and Countermeasures to Data Management in Metaverse
9.4 Privacy Threats and Countermeasures in Metaverse
9.5 Network‐Related Threats and Countermeasures in Metaverse
9.6 Economy‐Related Threats and Countermeasures in Metaverse
9.7 Threats to Physical World and Human Society and Countermeasures in Metaverse
9.8 Governance‐Related Threats and Countermeasures in Metaverse
9.9 Conclusions and Future Research Directions
Bibliography
10 IoT‐Assisted Metaverse Services
10.1 Why Need IoT for Metaverse Services
10.2 How to Use IoT for Metaverse DTs
10.3 A Dynamical Hierarchical Game‐Theoretical Approach for IoT‐Assisted Metaverse Synchronization
10.4 Conclusions and Future Research Directions
Bibliography
11 Quantum Technologies for the Metaverse: Opportunities and Challenges
11.1 Introduction
11.2 Preliminaries
11.3 Quantum Computing for a Faster Metaverse
11.4 Quantum Machine Learning for Contextual Metaverse
11.5 Quantum Communications for Secure Metaverse
11.6 Conclusions and Future Research Directions
Bibliography
12 The Metaverse with Life and Everything: An Overview of Privacy, Ethics, and Governance*
12.1 Introduction
12.2 Privacy and Security
12.3 Governance
12.4 Creation, Social Good, and Ethical Design
12.5 Conclusions and Future Research Directions
Bibliography
Index
End User License Agreement
List of Tables
Chapter 4
Table 4.1 3GPP traffic model [5].
Table 4.2 Weight for tiles.
Table 4.3 Parameters for simulation.
List of Illustrations
Chapter 2
Figure 2.1 Pokemon Go [5].
Figure 2.2 A concert in the Metaverse.
Figure 2.3 A meeting space in VIVE Sync.
Figure 2.4 Virtual collaboration in Microsoft Mesh by Microsoft. Licensed un...
Figure 2.5 Future collaborative work in the Metaverse by Microsoft. Licensed...
Figure 2.6 An illustration of a Zoom session.
Figure 2.7 The Solar System by Meta licensed under CC‐BY‐SA 3.0.
Chapter 3
Figure 3.1 Campus map of the Chinese University of Hong Kong, Shenzhen.
Figure 3.2 Simple use cases of
Newbie at CUHKSZ
and
CUHKSZ Metaverse
.
Figure 3.3 Voxel‐style administration building in
Newbie at CUHKSZ
.
Figure 3.4 Parkour game in
Newbie at CUHKSZ
.
Figure 3.5 Major introduction from SSE Dean in
Newbie at CUHKSZ
.
Figure 3.6 Task about safety awareness in
Newbie at CUHKSZ
.
Figure 3.7 Low poly administration building in
Newbie at CUHKSZ
.
Figure 3.8 Three‐layer Metaverse architecture of
CUHKSZ Metaverse
.
Figure 3.9 Key components of
CUHKSZ Metaverse
.
Figure 3.10 Screenshot of Metaverse viewer in
CUHKSZ Metaverse
.
Figure 3.11 Power‐saving mode and regional chat room in
CUHKSZ Metaverse
....
Figure 3.12 Map of token production rates in
CUHKSZ Metaverse
.
Figure 3.13 Day and night in
CUHKSZ Metaverse
.
Figure 3.14 User‐generated content editor in
CUHKSZ Metaverse
.
Figure 3.15 Pet editor in
CUHKSZ Metaverse
.
Figure 3.16 Store in
CUHKSZ Metaverse
.
Figure 3.17 Personal room decoration in
CUHKSZ Metaverse
.
Figure 3.18 Personal room in
CUHKSZ Metaverse
.
Figure 3.19 Billboard system in
CUHKSZ Metaverse
.
Figure 3.20 An example of the basketball court in
CUHKSZ Metaverse
.
Chapter 4
Figure 4.1 System model considered in this case study.
Figure 4.2 Adaptive AR communications and Metaverse user movement.
Figure 4.3 Model of a video frame and illustration of FoV.
Figure 4.4 Spherical mapping of tiles: (a) Sphere and (b) plane.
Figure 4.5 Evaluation settings.
Figure 4.6 QoE vs. number of users .
Figure 4.7 QoE vs. estimation error with different video quality levels.
Chapter 5
Figure 5.1 Outline of AI for the Metaverse, including the brief survey of AI...
Figure 5.2 A physical product/prototype can be integrated with DT via IoT an...
Figure 5.3 Outline of computer vision for the Metaverse, including the inves...
Figure 5.4 The SegNet architecture in Waldo93 / 207 images / Pixabay.
Figure 5.5 Computer vision for the Metaverse of autonomous driving.
Chapter 6
Figure 6.1 The real world and the Metaverse. An overview of the relationship...
Figure 6.2 Three Challenges for VR/AR/MR in enabling Metaverse. An overview ...
Figure 6.3 An overview of the progress of VR technology. Four examples (Cave...
Figure 6.4 An example of haptic feedback with a real‐time virtual avatar. Th...
Figure 6.5 The concept of redirected walking. This figure depicts the concep...
Figure 6.6 The concept of camera‐based detection for hand and face tracking....
Figure 6.7 An overview of the various AR technologies available. The figure ...
Figure 6.8 An illustration of an AR Virtual Global Landmark Concept. The fig...
Figure 6.9 An example of using mirror AR interaction in a Virtual World. The...
Figure 6.10 An example of MR through pass‐through VR. An illustration of hyb...
Figure 6.11 A conceptual figure of an MR Conference. This figure illustrates...
Chapter 7
Figure 7.1 Blockchain implementation areas in the Metaverse.
Figure 7.2 Structure of block in blockchain.
Figure 7.3 Transaction processing in blockchain.
Figure 7.4 Metaverse use cases.
Chapter 8
Figure 8.1 An illustration of real‐time physical–virtual synchronization bet...
Figure 8.2 Various types of computing infrastructure to support the computat...
Figure 8.3 A typical framework of the VR service market in the wireless edge...
Figure 8.4 The physical–virtual synchronization system in the vehicular Meta...
Chapter 9
Figure 9.1 The taxonomy of security threats and corresponding security count...
Figure 9.2 Comparison of hardware terminals for entering the web, mobile Int...
Figure 9.3 Illustration of blockchain‐enabled digital twin (DT)‐as‐a‐service...
Figure 9.4 Illustration of personal space in real and virtual worlds. (a) Fo...
Figure 9.5 An illustrative example of Sybil attack and DDoS attack in Metave...
Figure 9.6 Illustration of software‐defined network (SDN)‐enabled virtual ho...
Chapter 10
Figure 10.1 Virtual services in the Metaverse augment an individual's experi...
Figure 10.2 Virtual services in the Metaverse augment industry operations.
Figure 10.3 Relationship among IoT, DTs, VSPs, and Metaverse.
Figure 10.4 A dynamic hierarchical framework for IoT‐assisted Metaverse sync...
Figure 10.5 Comparison of the cumulative payoffs discounted at the present t...
Chapter 11
Figure 11.1 An overview of how the different quantum technologies can serve ...
Figure 11.2 The quantum teleportation protocol.
Figure 11.3 QML applications in the Metaverse.
Figure 11.4 Quantum communication approaches to enhance security.
Figure 11.5 Quantum communication applications in the Metaverse.
Chapter 12
Figure 12.1 Metaverse festival.
Figure 12.2 An example of a modular‐based Metaverse architecture motivated t...
Guide
Cover
Table of Contents
Title Page
Copyright
Dedication
Editors' Biography
List of Contributors
Preface
Acknowledgments
Introduction
Begin Reading
Index
End User License Agreement
Pages
ii
iii
iv
v
xvi
xvii
xviii
xix
xx
xxi
xxii
xxiii
xxiv
xxv
xxvi
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
IEEE Press
445 Hoes Lane Piscataway, NJ 08854
IEEE Press Editorial Board
Sarah Spurgeon,
Editor in Chief
Jón Atli Benediktsson
Behzad Razavi
Jeffrey Reed
Anjan Bose
Jim Lyke
Diomidis Spinellis
James Duncan
Hai Li
Adam Drobot
Amin Moeness
Brian Johnson
Tom Robertazzi
Desineni Subbaram Naidu
Ahmet Murat Tekalp
Metaverse Communication and Computing Networks
Applications, Technologies, and Approaches
Edited by
Dinh Thai HoangUniversity of Technology Sydney, Australia
Diep N. NguyenUniversity of Technology Sydney, Australia
Cong T. NguyenDuy Tan University, Vietnam
Ekram HossainUniversity of Manitoba, Canada
Dusit NiyatoNanyang Technological University, Singapore
Copyright © 2024 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per‐copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750‐8400, fax (978) 750‐4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748‐6011, fax (201) 748‐6008, or online at http://www.wiley.com/go/permission.
Trademarks: Wiley and the Wiley logo are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries and may not be used without written permission. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc. is not associated with any product or vendor mentioned in this book.
Limit of Liability/Disclaimer of WarrantyWhile the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762‐2974, outside the United States at (317) 572‐3993 or fax (317) 572‐4002.
Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.
Library of Congress Cataloging‐in‐Publication Data applied for:
Hardback ISBN: 9781394159987
Cover Design: WileyCover Image: © Olga Siletskaya/Getty Images
To my family
— Dinh Thai Hoang
To my family
— Diep N. Nguyen
To my family
— Cong T. Nguyen
To my parents
— Ekram Hossain
To my family
— Dusit Niyato
Editors' Biography
Dinh Thai Hoang received his PhD degree from the School of Computer Science and Engineering, Nanyang Technological University, Singapore, in 2016. He is currently a faculty member at the University of Technology Sydney (UTS), Australia. Over the past 10 years, he has significantly contributed to advanced wireless communications and networking systems. This is evidenced by his excellent record with one patent filed by Apple Inc., two authored books, one edited book, four book chapters, more than 80 IEEE Q1 journals, and 60 flagship IEEE conference papers in the areas of communications and networking. Most of his journal papers have been published in top IEEE journals, including IEEE JSAC, IEEE TWC, IEEE COMST, and IEEE TCOM. Furthermore, his research papers have had a high impact, as evidenced by nearly 14,000 citations with an h‐index of 44 (according to Google Scholar) over the past 10 years. Since joining UTS in 2018, he has received more than AUD 3 million in external funding and several precious awards, including the Australian Research Council Discovery Early Career Researcher Award for his project “Intelligent Backscatter Communications for Green and Secure IoT Networks” and IEEE TCSC Award for Excellence in Scalable Computing for Contributions on “Intelligent Mobile Edge Computing Systems” (Early Career Researcher). Alternatively, he is the lead author of two authored books, “Ambient Backscatter Communication Networks,” published by Cambridge Publisher in 2020 and “Deep Reinforcement Learning for Wireless Communications and Networking,” published by IEEE‐Wiley Publisher in 2022. He is currently an Editor of IEEE TMC, IEEE TWC, IEEE TCCN, IEEE TVT, and IEEE COMST.
Diep N. Nguyen is a faculty member of the Faculty of Engineering and Information Technology, University of Technology Sydney (UTS). He received ME and PhD in Electrical and Computer Engineering from the University of California San Diego (UCSD) and the University of Arizona (UA), respectively. Before joining UTS, he was a DECRA Research Fellow at Macquarie University, a member of technical staff at Broadcom (California), ARCON Corporation (Boston), consulting the Federal Administration of Aviation on turning detection of UAVs and aircraft, US Air Force Research Lab on anti‐jamming. He has received several awards from LG Electronics, the University of California San Diego, the University of Arizona, US National Science Foundation, and Australian Research Council, including nominations for the outstanding RA (2013) awards, the best paper award at the WiOpt conference (2014), Discovery Early Career Researcher Award (DECRA, 2015), and outstanding Early Career Researcher award (SEDE, University of Technology Sydney, 2018). His recent research interests are in the areas of computer networking, wireless communications, and machine learning application, with an emphasis on systems' performance and security/privacy. Dr. Nguyen is a senior member of IEEE and an editor/associate editor of the IEEE Transactions on Mobile Computing, IEEE Access, Sensors journal, and IEEE Open Journal of the Communications Society (OJ‐COMS).
Cong T. Nguyen received his BE degree in Electrical Engineering and Information Technology from Frankfurt University of Applied Sciences in 2014, his MSc in Global Production Engineering and Management from the Technical University Berlin in 2016, and his PhD in Information Technology from University of Technology Sydney in 2023. He is currently with Duy Tan University, Vietnam. His research interests include blockchain technology, operation research, game theory, and optimization.
Ekram Hossain is a professor and an associate head (Graduate Studies) at the Department of Electrical and Computer Engineering, University of Manitoba, Canada. He is a member (Class of 2016) of the College of the Royal Society of Canada. His current research interests include design, analysis, and optimization of 6G cellular wireless networks. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science for six years in a row from 2017 to 2022. He received the 2017 IEEE ComSoc Technical Committee on Green Communications and Computing Distinguished Technical Achievement Recognition Award “for outstanding technical leadership and achievement in green wireless communications and networking.” He has won several research awards, including the 2017 IEEE Communications Society Best Survey Paper Award and the 2011 IEEE Communications Society Fred Ellersick Prize Paper Award. He served as the editor‐in‐chief for the IEEE Communications Surveys and Tutorials from 2012 to 2016 and the editor‐in‐chief for IEEE Press. He was a distinguished lecturer of the IEEE Communications Society and the IEEE Vehicular Technology Society. He was an elected member of the board of governors of the IEEE Communications Society for the term from 2018 to 2020. He was elevated to an IEEE fellow “for contributions to spectrum management and resource allocation in cognitive and cellular radio networks.” He is a fellow of the Canadian Academy of Engineering and a fellow of the Engineering Institute of Canada.
Dusit Niyato is a professor at the School of Computer Science and Engineering, Nanyang Technological University, Singapore. He received BE from King Mongkuk's Institute of Technology Ladkrabang (KMITL), Thailand, in 1999 and a PhD in Electrical and Computer Engineering from the University of Manitoba, Canada, in 2008. Dusit's research interests are in the areas of distributed collaborative machine learning, the Internet of Things (IoT), edge intelligent metaverse, mobile and distributed computing, and wireless networks. Dusit won the Best Young Researcher Award of IEEE Communications Society (ComSoc) Asia Pacific and the 2011 IEEE Communications Society Fred W. Ellersick Prize Paper Award and the IEEE Computer Society Middle Career Researcher Award for Excellence in Scalable Computing in 2021 and Distinguished Technical Achievement Recognition Award of IEEE ComSoc Technical Committee on Green Communications and Computing 2022. Dusit also won a number of best paper awards, including IEEE Wireless Communications and Networking Conference (WCNC), IEEE International Conference on Communications (ICC), IEEE ComSoc Communication Systems Integration and Modelling Technical Committee, and IEEE ComSoc Signal Processing and Computing for Communications Technical Committee 2021. Currently, Dusit is serving as editor‐in‐chief of IEEE Communications Surveys and Tutorials, an area editor of IEEE Transactions on Vehicular Technology, editor of IEEE Transactions on Wireless Communications, associate editor of IEEE Internet of Things Journal, IEEE Transactions on Mobile Computing, IEEE Wireless Communications, IEEE Network, and ACM Computing Surveys. He was a guest editor of the IEEE Journal on Selected Areas on Communications. He was a distinguished lecturer of the IEEE Communications Society for 2016–2017. He was named the 2017–2021 highly cited researcher in computer science. He is a fellow of IEEE and a fellow of IET.
List of Contributors
Mshari Aljumaie
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
and
Department of Information Technology
Taif University
Taif
Saudi Arabia
Carlos Bermejo
Department of Computer Science and Engineering, School of Engineering
The Hong Kong University of Science and Technology
Hong Kong SAR
China
Sweta Bhattacharya
School of Information Technology and Engineering
Vellore Institute of Technology
Tamil Nadu
India
Tristan Braud
Division of Integrative Systems and Design
Hong Kong University of Science and Technology
Hong Kong SAR
China
Wei Cai
School of Science and Engineering
The Chinese University of Hong Kong
Shenzhen, Shenzhen
China
Dimitris Chatzopoulos
School of Computer Science
University College Dublin
Dublin
Ireland
Mahdi Chehimi
Wireless@VT
Bradley Department of Electrical and Computer Engineering, Virginia Tech
Arlington, VA
USA
Rajeswari Chengoden
School of Information Technology and Engineering
Vellore Institute of Technology
Tamil Nadu
India
Hieu Chi Nguyen
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
Nam H. Chu
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
Tan Do‐Duy
Department of Computer and Communication Engineering
Ho Chi Minh City University of Technology and Education
Ho Chi Minh City
Vietnam
Haihan Duan
School of Science and Engineering
The Chinese University of Hong Kong
Shenzhen, Shenzhen
China
Eryk Dutkiewicz
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
Thippa Reddy Gadekallu
School of Information Technology and Engineering
Vellore Institute of Technology
Tamil Nadu
India
and
Department of Electrical and Computer Engineering
Lebanese American University
Byblos
Lebanon
Zhu Han
Department of Electrical and Computer Engineering
University of Houston
Houston, TX
USA
Yue Han
Alibaba‐NTU Singapore Joint Research Institute
Nanyang Technological University
Singapore
Pawan Kumar Hegde
School of Information Technology and Engineering
Vellore Institute of Technology
Tamil Nadu
India
Dinh Thai Hoang
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
Pan Hui
Department of Computer Science and Engineering, School of Engineering
The Hong Kong University of Science and Technology
Hong Kong SAR
China
Dong In Kim
Department of Electrical and Computer Engineering
Sungkyunkwan University
Suwon, Gyeonggi‐do
Korea
Cyril Leung
Department of Electrical and Computer Engineering
University of British Columbia
Vancouver, BC
Canada
Lik‐Hang Lee
Department of Industrial and Systems Engineering (ISE)
The Hong Kong Polytechnic University
Hong Kong SAR
China
Chin‐Teng Lin
Computational Intelligence and Brain‐Computer Interface,
Australian Artificial Intelligence Institute
University of Technology Sydney
Ultimo, NSW
Australia
Dongxiao Liu
Department of Electrical and Computer Engineering
University of Waterloo
Waterloo, ON
Canada
Tom H. Luan
School of Cyber Science and Engineering
Xi'an Jiaotong University
Xi'an, Shaanxi
China
Praveen Kumar Reddy Maddikunta
School of Information Technology and Engineering
Vellore Institute of Technology
Tamil Nadu
India
Shiwen Mao
Department of Electrical and Computer Engineering
Auburn University
Auburn, AL
USA
Dusit Niyato
School of Computer Science and Engineering
Nanyang Technological University
Singapore
Cong T. Nguyen
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
Diep N. Nguyen
School of Electrical and Data Engineering
University of Technology Sydney
Ultimo, NSW
Australia
Quoc‐Viet Pham
School of Computer Science and Statistics
Trinity College Dublin
Dublin
Ireland
Xuan‐Qui Pham
ICT Convergence Research Center
Kumoh National Institute of Technology
Gumi
Korea
Walid Saad
Wireless@VT
Bradley Department of Electrical and Computer Engineering, Virginia Tech
Arlington, VA
USA
Xuemin Shen
Department of Electrical and Computer Engineering
University of Waterloo
Waterloo, ON
Canada
Zhou Su
School of Cyber Science and Engineering
Xi'an Jiaotong University
Xi'an, Shaanxi
China
Thien‐Huynh The
Department of Computer and Communication Engineering
Ho Chi Minh City University of Technology and Education
Ho Chi Minh City
Vietnam
Nancy Victor
School of Information Technology and Engineering
Vellore Institute of Technology
Tamil Nadu
India
Yuntao Wang
School of Cyber Science and Engineering
Xi'an Jiaotong University
Xi'an, Shaanxi
China
Rui Xing
School of Cyber Science and Engineering
Xi'an Jiaotong University
Xi'an, Shaanxi
China
Minrui Xu
School of Computer Science and Engineering
Nanyang Technological University
Singapore
Hongliang Zhang
School of Electronics
Peking University
Beijing
China
Ning Zhang
Department of Electrical and Computer Engineering
University of Windsor
Windsor, ON
Canada
Pengyuan Zhou
School of Cyber Science and Technology
University of Science and Technology of China
Hefei
China
Howe Yuan Zhu
Computational Intelligence and Brain‐Computer Interface
Australian Artificial Intelligence Institute
University of Technology Sydney
Ultimo, NSW
Australia
Preface
Recently, Metaverse has gained paramount interest and huge investment from the tech industry. Microsoft acquired Activision Blizzard for $70 billion in 2022 to set its first footsteps in the Metaverse game development race. Along with its huge investment in AR, one of the core technologies of Metaverse, Google has invested $39.5 million in a private equity fund for all Metaverse projects. Nvidia has created Omniverse, a developing tool for Metaverse applications. Besides huge investments from big tech companies, the economic activities of virtual worlds are also significant, with transactions that exceed the magnitude of millions of dollars. As a result, there is no doubt that the Metaverse will become one of the most prominent directions of development in both industry and academia. However, the development of the Metaverse, especially in academia, is still in a nascent stage. Currently, researchers are striving to judge the shape and boundary of the future Metaverse. They are only able to envision some of its possible characteristics, such as open space, decentralization, human–computer interaction experience, digital assets, and digital economy. Moreover, Metaverse applications are expected to face various challenges such as massive resource demands, ultralow latency requirements, interoperability among applications, and security and privacy concerns. Given the above, this book aims to provide a comprehensive overview of Metaverse and discuss its enabling technologies and how these technologies can be utilized to develop Metaverse applications.
Sydney, Australia
Dinh Thai Hoang
Diep N. Nguyen
Cong T. Nguyen
Ekram Hossain
Dusit Niyato
Acknowledgments
The contribution made by Dr. Dinh Thai Hoang was supported in part by the Australian Research Council's Discovery Projects funding scheme (project DE210100651).
The contribution done by Prof. Dusit Niyato was supported in part by the National Research Foundation (NRF), Singapore, and Infocomm Media Development Authority under the Future Communications Research Development Programme (FCP); DSO National Laboratories under the AI Singapore Programme (AISG Award No: AISG2‐RP‐2020‐019); and under DesCartes and the Campus for Research Excellence and Technological Enterprise (CREATE) programme.
Introduction
Edited by: Dinh Thai Hoang, Diep N. Nguyen, Cong T. Nguyen, Ekram Hossain, and Dusit Niyato
The term “Metaverse” refers to next‐generation Internet applications that aim to create virtual 3D environments where humans can interact with each other and the applications' functionalities via digital avatars. Although the original concept dates back to 1992, Metaverse has recently attracted paramount attention due to the huge potential to rival, or even replace, conventional Internet applications in the near future.
However, the development of the Metaverse, especially in academia, is still in a nascent stage. Currently, researchers are striving to judge the shape and boundary of the future Metaverse. They can only envision some of its possible characteristics, such as open space, decentralization, human–computer interaction experience, digital assets, and digital economy. Moreover, Metaverse applications are expected to face various challenges, such as massive resource demands, ultralow latency requirements, application interoperability, and security and privacy concerns.
Given the above, this book aims first to introduce the emerging paradigm of Metaverse, which is expected to pave the way for the evolution of the future Internet. The book also provides a comprehensive review of the state‐of‐the‐art research and development covering different aspects of Metaverse for a wide range of readers, from general readers to experts. Advanced knowledge including innovative models, techniques, and approaches to overcome the limitations and challenges in developing Metaverse are then discussed. Finally, emerging applications of Metaverse are presented, along with the related challenges and open issues.
1Metaverse: An Introduction
Lik‐Hang Lee1, Dimitris Chatzopoulos2, Pengyuan Zhou3, and Tristan Braud4#
1Department of Industrial and Systems Engineering (ISE), The Hong Kong Polytechnic University, Hong Kong SAR, China
2School of Computer Science, University College Dublin, Dublin, Ireland
3School of Cyber Science and Technology, University of Science and Technology of China, Hefei, China
4Division of Integrative Systems and Design, Hong Kong University of Science and Technology, Hong Kong SAR, China
After reading this chapter you should be able to:
Understand the current trends and challenges that building such a virtual environment will face.
Focus on three major pillars to guide the development of the Metaverse: privacy, governance, and ethical design and to guide the sustainable yet acceptable development of the Metaverse.
Illustrate a preliminary modular‐based framework for an ethical design of the Metaverse.
1.1 Introduction
The term “Metaverse” was first introduced to the public in 1992 by Neal Stephenson in his work of science fiction, “Snow Crash.” The main characters of the book are shown to coexist with their avatars in a world that is an integration of the virtual and the real, and it is populated by persistent virtual entities that are superimposed on our actual surroundings. People are able to execute a wide variety of immersive activities in this integrated reality.
Several noticeable instances of this trend include people getting together with their friends in a different location, working jointly with their coworkers, and participating in shared virtual experiences (e.g. dating and virtual fitting). In other words, diverse digital or virtual contents originating from cyberspace will eventually go beyond the boundary of 2D displays in the Internet that we are now using and gradually make their way into three‐dimensional (3D) settings.
As was said before, coincidentally, the projected environment is congruent with Mark Weiser's vision of ubiquitous computing in 1991: computer services would be integrated into a multitude of facets of our lives, and users will have access to virtual information whenever and wherever they choose. With such a compelling vision, the landscape of ubiquitous computing has been advanced throughout the course of the previous three decades by the proliferation of computing devices. These computing devices include laptop computers, smartphones, the Internet of Things (IoTs), and intelligent wearables.
According to Milgram and Kishino's Reality‐Virtuality Continuum [16], the current cyberspace has undergone significant development in recent years, and recent attempts have been made to provide human users with services and digital experiences by means of virtual environments such as augmented reality (AR) and virtual reality (VR). Although no one can say for certain what the Metaverse will bring about once it is fully realized, recent pre‐metaverse apps have most likely identified AR and VR on smartphones as the major testbed for immersive user experiences. Pokémon Go, for example, has become the most popular AR program on ubiquitous smartphones, astoundingly with 1 billion downloads, while Google Cardboard is bringing VR content to mainstream audiences (for example, YouTube VR) [4].
As such, the term “Metaverse” refers to a blended space at the intersection between physical and digital in which multiple users can concurrently interact with a persistent and unified computer‐generated environment, and other users. This space has the potential to become the next important milestone in the development of cyberspace as it exists today.
It is worth noting that modern devices that enable entrance to Metaverse get access to multiple types of users' data. Also services based on artificial intelligence (AI) use derivatives of data generated by users in their function, making data the new commodity that spawns a lucrative, fast‐growing industry.
This introductory chapter focuses primarily on discussing the evolution of the Metaverse as well as the difficulties that have been encountered. First, we will provide a concise overview of the evolution of cyberspace as well as the importance of technological enablers. As a result, our bottom‐up methodology places an emphasis on the following three crucial technological enablers for the Metaverse: networks, systems, and users. In addition, we emphasize a number of essential challenges, both from a technical and an ecosystemic point of view, that are necessary for the construction and maintenance of the Metaverse.
1.2 The Metaverse: Fantasy, Text, 3D Worlds
It should come as no surprise that technological advancements always play the role of an essential constituent in the construction of the subsequent phase of cyberspace's evolution into the Metaverse. Before we get to the status quo, also known as the pre‐Metaverse (V), we will have passed through four distinct phases in rapid succession. The stages are as follows: (i) Literature: imaginary worlds described in written works; (ii) Text‐based virtual worlds: computer‐mediated cyberspace solely driven by text‐based interaction; (iii) 3D Virtual Worlds: enriched cyberspace with graphics; and (vi) AR and VR on Ubiquitous Devices: virtual‐physical blended worlds appearing on mobile phones, tablets, and smartglasses. In other words, the above four phases have been triggered by technological advancement, and they are interconnected.
At the beginning of the process, Literature evolves into the limitless area of imagination that is required for technological development. Even though the technologies were not quite developed enough at the time, some of the most representative novels are “The Master Key,” “Dungeons & Dragons,” “Neuromancer,” and “Snow Crash.” These novels depict what it might be like to have immersive experiences. Multi‐User Dungeon games, often known as MUD games, have been popular since the introduction of personal computers (II), and they enable user interaction via the use of text. Next, in 1995, the very first 3D virtual environment, known as Active World, was released. This occurred when personal computers became capable of running computer graphics programs (III). Multiplayer 3D online games like Second Life and Minecraft have become more popular as a result of the proliferation of online users. In addition, the proliferation of smartphones in the latter part of the 2000s (VI) laid the groundwork for the mobile AR and VR applications that were discussed before.
After 2015 (V), the commercialization of AR and VR headsets, such as Google Glass and Meta Oculus, will enable users to be enclosed by computer‐mediated environments and to see digital overlays in virtual‐physical blended environments, such as VR Chat, Horizon Workrooms, and HoloMeeting, respectively. It is important to note that the pandemic that has been going on since 2020 can be regarded as one of the “experiments” that has been carried out on the largest scale in the history of the world: are people willing to accept the continued movement of various life functions into virtual environments? Obviously, we should. Certain visionary multinational companies in the technology sector, such as Microsoft and Meta, are promoting virtual collaboration spaces for everyone via inexpensive AR and VR ubiquitous devices. This includes both end users and businesses. As a result, we anticipate that the further progressions of cyberspace that incorporate immersiveness, also known as immersive cyberspace, will need to take into consideration various technological enablers.
The subsequent paragraphs in this chapter provide a reality check on the various technological enablers and the issues they provide. We take a bottom‐up approach to discuss the three most important aspects, which have been inherited from the viewpoints of ubiquitous computing in particular: the network and mobile edge, system interoperability, and user‐centric immersive design, which are representing the network, the system, and human users. We are aware that the breadth of the technological enablers for the Metaverse [14]) (such as artificial intelligence, hyperledger, computer vision, and robotics) may transcend beyond the boundaries of our current conversation.
1.3 The Rise of Edge Computing
In order to deliver the same degree of experience as reality, it is vital in the Metaverse to ensure that the users have the sense of being immersed in the environment. Latency, for example the motion to photon (MTP) latency,1 is one of the most critical factors to consider. According to what the researchers have discovered, the MTP latency requirement has to be below the human perceptible limit in order for users to be able to engage with holographic scenes and objects in a smooth and natural manner [15].
For example, the registration procedure for AR may create nausea and dizziness because of excessive latency, which typically results in virtual items trailing behind the desired location. As a result, lowering latency is essential for the Metaverse, particularly in settings where real‐time data processing is required, for example, real‐time AR overlapping with the actual environment, such as in AR surgeries. On the other hand, the Metaverse often necessitates a computation that is too demanding for mobile devices, which severely restricts its usefulness.
1.3.1 Offloading
The process of offloading is often utilized as a means of relieving the burden of compute and memory in this context, despite the fact that doing so incurs extra delay in the networking process. As a result, achieving a satisfactory compromise is essential in order to make the offloading process visible to the end users, which is regrettably not a simple task. For instance, while presenting a locally navigable 1 MTP, latency refers to the amount of time that passes between an action taken by the user and the moment when that action's related consequence is reflected on the screen.
It is required to have an egocentric view that is two times wider than the Field‐of‐View (FOV) of the headset in order to compensate for the networking delay that occurs during offloading. However, there is a conflict between the needed user's egocentric view(s) and the networking latency. Longer networking latency can be caused by a bigger size of display and resolution, and thus the streaming of more digital content, both of which result in even longer networking delay. As a result, a solution that improves physical deployment may be a more practical option than one that focuses just on resource orchestration. Because of the fluctuating and unexpected nature of the high latency, cloud offloading is unable to constantly achieve the optimal balance. This results in long‐tail latency performance, which has a negative influence on the user experience [5].
Therefore, a supplementary solution is required in order to ensure that users will have a consistent and immersive experience inside the Metaverse. Edge computing, which computes, stores, and transmits the data physically closer to end‐users and their devices, can reduce the user‐experienced latency when compared with cloud offloading. Edge computing works by computing, storing, and transmitting the data physically closer to end‐users and their devices. As early as 2009, Satyanarayana et al. [20] noticed that installing powerful cloud‐like infrastructure only one wireless hop away from the end users' mobile devices, namely Cloudlet, might completely change the course of the game.
The most recent iterations of mobile AR frameworks have begun to use edge‐based solutions in an effort to boost the overall performance of Metaverse applications. For instance, EdgeXAR is a mobile AR framework that uses the advantages of edge offloading to achieve lightweight tracking with six degree‐of‐freedom (DOF) while reducing the offloading delay from the user's view [25]. Additionally, edge‐facilitated augmented vision in vehicle‐to‐everything (EAVVE) provides a new system of cooperative AR vehicular perception between multiple drivers, which are remarkably assisted by edge servers. This system helps to lower the total offloading latency and compensates for the inadequate processing capability that is present in vehicles [26].
1.3.2 Scale to Outdoor
Users are able to have a more engaging and immersive experience at higher frame rates without compromising the level of details present in immersive settings by offloading processing to an edge server (for example, a high‐end personal computer). On the other hand, such systems can only be used in interior settings where the user's movement is restricted. It is essential to have seamless movement outside in order to enable for a Metaverse experience that is both really and completely ubiquitous. With the development of 5G and 6G, it is anticipated that multiaccess edge computing, also known as MEC, will enhance the Metaverse user experience. MEC can deliver standard and universal edge offloading services, which is just one hop away from cellular‐connected user devices, such as AR smartglasses.
Not only does it have the potential to cut down on the round‐trip time (RTT) of packet delivery, but it also paves the way for near real‐time orchestration of multiuser interactions. MEC is essential for outdoor Metaverse services to have in order to perceive the specifics of the local situation and organize intimate collaborations between users or devices in close proximity to one another. For instance, 5G MEC servers may manage the AR content of adjacent users with just one hop of packet transfer. This enables real‐time user engagement for social AR apps like “InGress2.” Utilizing MEC to improve the experience of the Metaverse has gained interest from the academic community. Also, MEC has been employed by several Metaverse enterprises to enhance the experience of their customers.3
1.4 Universality, Interoperability, and Openness
When this chapter was being prepared, the majority of the plans and initiatives pertaining to the Metaverse were separate projects that were entirely controlled by a single organization. In spite of the fact that such fragmentation makes it possible to experiment with many thoughts and ideas during an experimental age, this approach cannot be maintained over the long run. Even more so, we contend that interoperability and openness will be the two key factors that will determine the success or the failure of the Metaverse's push for global acceptance.
1.4.1 Using the World Wide Web as an Illustration
In multitudinous ways, the Metaverse may be seen as the next stage of development after the World Wide Web in terms of a new type of content generation and dissemination. The World Wide Web was conceptualized from the very beginning with decentralization and interoperability [2] in mind. A website may be created by almost anybody or any organization provided they have enough technical knowledge, e.g. a computer engineer or programmer, and access to the Internet. The operation of the World Wide Web is not dependent on any centralized body, and the more centralized services (such as Domain Name Registration) are only handy extensions to a wholly decentralized technological base. In point of fact, Tim Berners‐personal Lee's computer at the European Organization for Nuclear Research (CERN) was the host of the very first website that was ever made available to the public. The fact that there is a very low barrier to entry, in addition to the fact that the user has full control over what is published, gave people ownership of the medium, which contributed to the success of the Web.
Interoperability and openness were critical factors in the development of the Web into the pervasive technology that it is happening. On the other hand, this resulted in a number of different actors inventing their own versions of the HTML language and rendering engines. Tim Berners‐Lee established the World Wide Web Consortium (W3C)4 in 1994 with the intention of promoting interoperability throughout the industry and, more crucially, maintaining the vendor‐neutrality of the Internet. Nowadays, the W3C serves as an organization for standardization. Under the direction of its members, it writes and sets the standards that govern the World Wide Web.
1.4.2 Realizing the Potential of Interoperability in the Metaverse
The Metaverse needs to be based on a paradigm that is analogous to that of the World Wide Web, in which users may access a wide variety of virtual worlds that are hosted by a variety of entities by means of devices and browsers that have been developed by a large number of businesses and organizations. On the other hand, the Metaverse has properties that have a substantial impact on this operation. Before it was made available to the general public, the World Wide Web was a technology that was only developed and administered by a single organization.
Comparatively, there have been several efforts to construct the Metaverse since the late 1990s. These attempts began with the French virtual world “Deuxi'eme Monde”5 (1997) (1997) and continued with the more well‐known “Second Life6” (2003). In contrast to the World Wide Web, the majority of these initiatives were developed using the concept of massively multiplayer online games. In this approach, a single corporation retains complete control over the material that is published on their platform.
More recent hyperledger‐based concepts, such as Decentraland,7 take things one step further by storing material on distributed servers (IPFS) and tracking ownership using a public hyperledger. However, the online platform that the user uses to access the Metaverse world continues to be reliant on the organization that is its parent, and there is very little interchange between the web platform and other platforms. However, we need to highlight that deleting data from decentralized storage mechanisms may be challenging but necessary to comply with the “right to be forgotten” that has been advocated for by several organizations all over the globe. In light of the growing number of Metaverse initiatives that are incompatible with one another, it is more important than ever to build standardizing organisms that are able to solve the following aspects:
The opportunity for anybody to build a server and run a virtual world that is linked to the rest of the Metaverse.
The ability to access the Metaverse using any device and browser as long as they adhere to a predetermined specification (e.g. client‐based rendering).
Keeping a record of who owns each piece of digital property across all of the servers and the clients.
Allowing avatars to provide access to their data in exchange for credit in Metaverse spaces.
Making it possible for a single avatar to communicate with other avatars located on other servers.
Providing users with the ability to produce, display, buy, sell, and remove digital assets inside the Metaverse.
Integrating inter‐Metaverse (in equivalence to interplanetary) learning mechanisms [
19
,
23
] that will allow users, via their avatars, to update and use personalized models that are adapted to different virtual worlds within the Metaverse.
It is essential for users to have these traits in order to take ownership of the Metaverse and to encourage ubiquitous adoption, which will pave the road for a Metaverse that is omnipresent.
1.4.3 The Argument in Favor of Immersive Technologies
Both ubiquitous computing and the Metaverse rely heavily on technologies that provide users with an immersive experience, such as AR and VR. When it comes to ubiquitous computing, they make it possible for greater contextualization of data to be visualized, and when it comes to the Metaverse, they help users feel more immersed in the virtual environment they are in.
A common way to think about these technologies is as a spectrum spanning from realism to complete virtuality, with applications integrating digital material with a physical setting to varying degrees. This spectrum may be thought of as a continuum. Because the Metaverse is still in its infancy, there is no concrete definition of the extent to which these technologies should interact with the real world. This ambiguity will undoubtedly have an effect on interoperability, since certain Metaverse programs may be firmly rooted at a specific physical place, while others may be fully virtual [6] and accessible through a conventional desktop computer. According to the findings of a research on the creation of an AR Metaverse campus [3], an entirely virtual experience should be replicated of the real‐world setting, via the use of digital twins, which make it possible for geolocalized experiences to be accessed by people located elsewhere. On the other hand, in a manner that is analogous to the problems that have been discussed so far, the only entity that can definitively specify how to produce such duality is a standardization organism.
1.5 Steps Toward Mobile User Interaction Within the Metaverse
Users should have their own channels to convert their intents into actions in virtual or immersive scenarios whenever and wherever they choose [11]. This is especially important in light of the fact that the Metaverse will ultimately permeate every facet of everyday activities. The already available AR and VR apps for smartphones provide light on the widespread acceptance of virtual material that is layered on the real environment. Smartphones cannot compare to the level of immersion provided by the latest generation of Metaverse devices, such as AR and VR headsets. Nevertheless, modern headsets do not provide users with effective options for user input. Under the premise that interfaces are increasing smaller in size, user interaction with virtual contents in the Metaverse becomes more complex and laborious as a result.
A great number of research prototypes are working toward the goal of enhancing unique input channels that incorporate user mobility. For example, Google's Jacquard8 incorporates integrated sensors into clothing, which augments our everyday clothes as a huge touch interface for user interaction that is similar to that of a touchscreen. Wearable addendums are another sort of mobile input. These addendums expand users' bodies as the focus of user engagement with virtual contents. Examples of wearable addendums include wristbands, gloves, and finger‐worn devices. There is still a considerable difference in input capabilities between sedentary solutions like the keyboard and mouse duos and the mobile input solutions that were discussed before, despite the fact that an increasing number of mobile input solutions have been offered in recent years [12].
In addition, the information that can be found in physical environments might be deemed limitless; however, the augmentation of the information that can be seen inside the relatively limited field of vision of headsets can be difficult [13]. As a result, we are going to have to perfect the way that virtual material is presented. In the event that this does not occur, users of the Metaverse who take a simplistic approach to the administration of virtual material may experience an information overflow, which will result in a considerable increase in the amount of time spent choosing augmentation. Context awareness is a notable method that involves taking into consideration the users, settings, and social dynamics [10]. Edge AI, such as recommendation systems, are able to analyze user context and provide the most relevant augmentation.
In addition, the current study on user contexts focuses largely on the users' five senses, which are presented in a plain and truthful manner throughout the research. Instead, further efforts should be taken to allow the user‐centric Metaverse to grasp the abstract but difficult‐to‐quantify sensations on top of the five senses. For example, a home with a dark and purple backdrop as opposed to a daunted house may elicit different feelings in the user (abstract feeling). In the Metaverse, a higher granularity of context‐awareness enables the provision of services that are both more exact and more personally tailored. Even if edge computing has the potential to enhance not just user experiences but also user privacy, Metaverse users will nevertheless leave behind a large number of user interaction traces in a cyberspace that blends the virtual and the real.
User privacy and design space are not fully explored when seen from the edge infrastructure. As a result of the fact that it is anticipated that users would participate in a variety of virtual activities, it follows that every incorrect pop‐ups of AR/VR entities might lead to new privacy issues. For instance, users may choose to leave their “augmented” discussions in the public realm of the immersive environment. There is a potential risk to users' privacy if every line of such discussion with numerous users is visually augmented [9]. The proprietors of virtual spaces need to work to strengthen information flows, maybe by having them be driven by contextual integrity. User and data contexts are impacted by a wide variety of elements, including the receiver of the data, the locations of the data, the sensitivity of the data, and so on. On the other hand, our knowledge of the design of information flows for highly diverse augmentation is quite limited, and that's not even taking into account the undiscovered types of augmentation that will emerge in the Metaverse.
1.6 Bringing Users' Profiles and Assets on the Metaverse
Notably, all the immersive technologies that will deliver entry points to Metaverse via multiple types of devices [22] will have access to potentially private users' data. These data are useful for
Producing personalised artificial intelligence (AI) models that will be enhance users'
quality of experience
(
QoE
) while being on the Metaverse.
Analyzing users' behavior and producing data of financial value (e.g. for advertising).
Representative Example A marathon athlete is trained for the next competition and is wearing a smart watch, smart shoes, and a VR headset while being remotely supervised by her coach in a virtual world that looks like the next marathon. The shoes are collecting data related to the athlete's steps and running technique, the watch gathers data associated with the current condition of her body, and the VR headset simulates the conditions of a marathon trail and virtually places the athlete together with other athletes in the trail. The athlete is training in virtual worlds, placing past versions of herself on the trail as different avatars to compare her performance with previously recorded attempts. All these data are used as input to a coaching service for athletes that simulate running environments, predict injuries, and assesses the health of the athlete. Unfortunately, the company that offers this service has access to the generated data.
The athlete should be able to decide which types of her data she is willing to share with the coaching company and the coaching company should employ privacy‐preserving techniques to process sensitive data [8]. Additionally, the athlete's devices should support on‐device privacy‐aware training techniques that guarantee that her private data are not shared with any centralized computing entity [18]. Moreover, in the scenario where the athlete is invited by fellow athlete to train together in a different virtual world that is hosted by a different company, the athlete should not only be able to join the virtual world, but she should also be able to “bring together her past selves” as avatars who are running in the new virtual world [7, 21]. Note that since the athlete is running for the first time in this new virtual world, the hosting company should be able to predict the performance of her past selves based on the produced AI models the athlete is bringing with her.
Last, considering that advertisements will be a major source income at Metaverse, the hosting company of the new virtual world should be able to get access to derivatives of the analytics produced by the previous world in order to present meaningful advertisements. Such information can be considered as a form of credit exchange between the worlds (i.e. similarly to the roaming service provided by mobile operators).
1.6.1 The Role of Distributed Ledgers, Smart Contracts, and Decentralized Storage
Distributed ledgers and smart contracts are developed from the Byzantine Generals' dilemma of achieving data consensus in a decentralized and trustless way. Remarkably, the first yet well‐known example is Bitcoin [17]. The development of the technical details of such technology is described in Chapter 7. Accordingly, all the aforementioned challenges can be tackled with decentralized Metaverse‐ready solutions that are based on distributed ledgers (e.g. the Ethereum blockchain [24]) and decentralized storage (e.g. IPFS [1]). AI models can be stored on IPFS and produced by IPLS [19] while being assisted by compute nodes [23]. Although multiple virtual worlds can share a distributed ledger for retrieving instantly information related to the users via specifically designed smart contracts, adding information to such ledger will be time demanding, depending on the employed consensus protocol and the size of the consensus network. Furthermore, an envisioned solution should require a set of smart contracts per user that will provide the flexibility to each user to control the information they are willing to share.
