Realizing the Metaverse
A Communications and Networking Perspective
1st Edition
Published on 22. November 2024
Book
Hardback
208 pages
978-1-394-18890-1 (ISBN)
Description
A guide to the challenges in making virtual reality, reality
The Metaverse, a version of the internet in which online interactions take place in real time within fully realized virtual spaces, has been promised as the next frontier in wireless communication. It has drawn huge investment from Silicon Valley and widespread media attention. However, the technologies required to make the Metaverse a reality are still in their infancy, and significant barriers must be overcome if this massive step is to be taken.
Realizing the Metaverse provides a systematic overview of these challenges and their likely solutions. Focusing on five key areas-infrastructure, access, intelligence, security, and future developments-it offers one of the first comprehensive, formalized treatments of the Metaverse as a nascent reality. It promises to be an integral contribution to the future development of Metaverse technologies.
Realizing the Metaverse readers will also find:
An editorial team with extensive research experience in the field
Detailed discussion of topics such as augmented reality (AR) adaptation, haptic feedback, artificial intelligence, and more
Enlightening discussion of open questions and future prospects for research
Realizing the Metaverse is ideal for graduate and advanced undergraduate students in wireless technology, network communications, and related fields, as well as for researchers and industry professionals involved with the Metaverse or adjacent technologies.
The Metaverse, a version of the internet in which online interactions take place in real time within fully realized virtual spaces, has been promised as the next frontier in wireless communication. It has drawn huge investment from Silicon Valley and widespread media attention. However, the technologies required to make the Metaverse a reality are still in their infancy, and significant barriers must be overcome if this massive step is to be taken.
Realizing the Metaverse provides a systematic overview of these challenges and their likely solutions. Focusing on five key areas-infrastructure, access, intelligence, security, and future developments-it offers one of the first comprehensive, formalized treatments of the Metaverse as a nascent reality. It promises to be an integral contribution to the future development of Metaverse technologies.
Realizing the Metaverse readers will also find:
An editorial team with extensive research experience in the field
Detailed discussion of topics such as augmented reality (AR) adaptation, haptic feedback, artificial intelligence, and more
Enlightening discussion of open questions and future prospects for research
Realizing the Metaverse is ideal for graduate and advanced undergraduate students in wireless technology, network communications, and related fields, as well as for researchers and industry professionals involved with the Metaverse or adjacent technologies.
More details
Language
English
Place of publication
United States
Publishing group
John Wiley & Sons Inc
Target group
Professional and scholarly
Dimensions
Height: 157 mm
Width: 239 mm
Thickness: 19 mm
Weight
414 gr
ISBN-13
978-1-394-18890-1 (9781394188901)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Wei Yang Bryan Lim | Zehui Xiong | Dusit Niyato
Realizing the Metaverse
A Communications and Networking Perspective
E-Book
11/2024
1st Edition
Wiley
€110.99
Available for download
Wei Yang Bryan Lim | Zehui Xiong | Dusit Niyato
Realizing the Metaverse
A Communications and Networking Perspective
E-Book
11/2024
1st Edition
Wiley
€110.99
Available for download
Persons
Wei Yang Bryan Lim, PhD, is a Wallenberg-NTU Presidential Postdoctoral Fellow, Nanyang Technological University, Singapore. He has received Best Paper Awards from the IEEE Wireless Communications and Networking Conference and the IEEE SPCC Technical Committee, and regularly serves as a reviewer for leading journals.
Zehui Xiong, PhD, is an Assistant Professor at Singapore University of Technology and Design. He has published extensively, won many prestigious career/paper awards, and served as the editor for many leading journals in the areas of Internet of Things, edge computing and intelligence. He serves as the Associate Director of Future Communications R&D Programme. He was featured on the list of Forbes Asia 30 under 30 in 2023.
Dusit Niyato, PhD, is a Professor in the School of Computer and Engineering, Nanyang Technological University, Singapore. He is an IEEE Fellow and serves as editor of numerous prestigious journals, including as editor-in-chief of IEEE Communications Surveys and Tutorials.
Junshan Zhang, PhD, is a Professor in the Electrical and Computer Engineering Department at the University of California, Davis, USA. He has researched and published extensively on information networks, data science, 5g, wireless communications, and related subjects, and currently serves as editor-in-chief for IEEE Transactions on Wireless Communication.
Xuemin (Sherman) Shen, PhD, is a University Professor in the Department of Electrical and Computer Engineering, University of Waterloo, Canada. He has published extensively on network resource management, wireless network security, Internet of Things, 5G, and more. He is a Fellow of the Engineering Institute of Canada, the Canadian Academy of Engineering, and the Royal Society of Canada, among others.
Zehui Xiong, PhD, is an Assistant Professor at Singapore University of Technology and Design. He has published extensively, won many prestigious career/paper awards, and served as the editor for many leading journals in the areas of Internet of Things, edge computing and intelligence. He serves as the Associate Director of Future Communications R&D Programme. He was featured on the list of Forbes Asia 30 under 30 in 2023.
Dusit Niyato, PhD, is a Professor in the School of Computer and Engineering, Nanyang Technological University, Singapore. He is an IEEE Fellow and serves as editor of numerous prestigious journals, including as editor-in-chief of IEEE Communications Surveys and Tutorials.
Junshan Zhang, PhD, is a Professor in the Electrical and Computer Engineering Department at the University of California, Davis, USA. He has researched and published extensively on information networks, data science, 5g, wireless communications, and related subjects, and currently serves as editor-in-chief for IEEE Transactions on Wireless Communication.
Xuemin (Sherman) Shen, PhD, is a University Professor in the Department of Electrical and Computer Engineering, University of Waterloo, Canada. He has published extensively on network resource management, wireless network security, Internet of Things, 5G, and more. He is a Fellow of the Engineering Institute of Canada, the Canadian Academy of Engineering, and the Royal Society of Canada, among others.
Content
About the Editors xiii
List of Contributors xvii
Foreword xix
Preface xxi
1 Introduction 1
Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Junshan Zhang, and Xuemin Sherman Shen
1.1 Introduction 1
1.1.1 Birth of the Metaverse 1
1.2 Architecture, Developments, and Tools of the Metaverse 4
1.2.1 Definition and Architecture 4
1.2.2 Current Developments 9
1.2.2.1 Massive Multiplayer Online Role-playing Games 10
1.2.2.2 Applications of the Metaverse 11
1.2.3 Tools, Platforms, and Frameworks 13
1.2.4 Summary and Lessons Learned 16
1.2.4.1 The Metaverse Cannot Be Realized by a Standalone Technology 16
1.2.4.2 Implementation Challenges 16
1.2.4.3 Standardized Protocols, Frameworks, and Tools 17
1.2.4.4 Metaverse Ecosystem and Economics 17
2 Communication and Computing in Edge-enabled Metaverse 19
Minrui Xu, Wei Chong Ng, Wei Yang Bryan Lim, and Dusit Niyato
2.1 Introduction 19
2.1.1 Rate-Reliability-Latency 3D Multimedia Networks 21
2.1.1.1 Resource Allocation for VR Streaming 25
2.1.1.2 Resource Allocation for AR Adaptation 28
2.1.1.3 Edge Caching for AR/VR Content 30
2.1.1.4 Hologram Streaming 31
2.1.2 Human-in-the-loop Communication 32
2.1.2.1 URLLC for the Tactile Internet 33
2.1.2.2 Semantic/Goal-aware Communication 34
2.1.3 Real-time Physical-Virtual Synchronization 36
2.1.3.1 Resource Allocation for Physical-Virtual Synchronization 37
2.1.3.2 Intelligent Edge Network-aided Virtual-Physical Synchronization 38
2.1.4 Lessons Learned 40
2.1.4.1 Efficient Immersive Streaming and Interaction 40
2.1.4.2 AI for Intelligent Edge Communication 40
2.1.4.3 Context-aware Immersive Content Delivery 40
2.1.4.4 Self-sustainable Physical-Virtual Synchronization 40
2.1.4.5 Decentralized Incentive Mechanism 41
2.2 Computation 41
2.2.1 The Cloud-Edge-End Computing Paradigm 43
2.2.2 Efficient AR/VR Cloud-Edge-End Rendering 45
2.2.2.1 Stochastic Demand and Network Condition 46
2.2.2.2 Stragglers at Edge Networks 48
2.2.2.3 Heterogeneous Tasks 49
2.2.3 Scalable AI Model Training 49
2.2.3.1 Parameter Pruning and Quantization 50
2.2.3.2 Low-rank Approximation 51
2.2.3.3 Knowledge Distillation 52
2.2.4 Privacy and Security 54
2.2.4.1 Trusted Execution Environment 55
2.2.4.2 Federated Learning 56
2.2.4.3 Adversarial Machine Learning 58
2.2.5 Lessons Learned 60
2.2.5.1 Adaptive AR/VR Cloud-Edge-End Rendering 60
2.2.5.2 On-demand and Generalized Model Compression 60
2.2.5.3 User-centric Computing 60
2.2.5.4 Secure Interoperable Computing 61
2.2.5.5 From Distribution to Decentralization 61
2.3 Summary 61
3 Advanced and Future Network Access Technologies for the Metaverse 63
Andrea Garbugli, Domenico Scotece, Luca Foschini, and Paolo Bellavista
3.1 Introduction 63
3.2 Edge-enabled Metaverse 64
3.2.1 Efficient Service Migration at the Edge 65
3.2.1.1 Multi-layer Container Migration 66
3.2.1.2 Metaverse-enabled Service Migration Architecture 68
3.2.1.3 Simulation Results 71
3.3 Ultra-low Latency Communications 73
3.3.1 ULL Networking Protocols 73
3.3.1.1 Time-sensitive Networking (TSN) 74
3.3.1.2 Wireless Networks: 5G and Wi-Fi 6 74
3.3.2 Acceleration Technologies 76
3.3.2.1 Linux eXpress Data Path (XDP) 76
3.3.2.2 Data Plane Development Kit (DPDK) 77
3.3.2.3 Remote Direct Memory Access (RDMA) 77
3.3.2.4 Integration for Metaverse Applications 78
3.3.3 SELENE: A Uniform Acceleration Middleware 78
3.3.3.1 SELENE: The APIs 79
3.3.3.2 SELENE: QoS Policies 81
3.3.3.3 SELENE: The Runtime 82
3.3.3.4 SELENE: Evaluation 85
3.3.3.5 Latency and Throughput Benchmarks 86
3.3.3.6 Lunar Streaming 90
3.4 Summary 92
4 How to Intelligentize the Metaverse 93
Zhe Zhang, Jialin Wu, Ziwen Jin, Xidong Wang, Jiawen Kang, Yanchao Zhao, and Yi Wu
4.1 Seven-layer Model of the Intelligentized Metaverse 93
4.1.1 Experience Layer 93
4.1.2 Exploration and Discovery Layer 94
4.1.3 Creator Economy Layer 95
4.1.4 Spatial Computing Layer 95
4.1.5 Decentralized Layer 95
4.1.6 Human-Computer Interaction Layer 96
4.1.7 Infrastructure Layer 96
4.2 AI for the Metaverse 96
4.2.1 Avatar Creation 96
4.2.2 Empowering 3D Chatbots 97
4.2.3 Language Processing 97
4.2.4 Enabling Human-Computer Interactions 97
4.2.5 3D Scene Rendering 98
4.3 Edge AI for the Metaverse 98
4.3.1 Edge AI Architectures 98
4.3.1.1 Cloud-edge Collaboration Architecture 98
4.3.1.2 Decentralized Architecture 99
4.3.1.3 Federated Learning Architecture 100
4.3.2 How Does Edge AI Contribute to Creating the Metaverse? 100
4.3.2.1 Unique Challenges in the Edge AI-empowered Metaverse 100
4.3.2.2 Benefits of Edge AI for the Metaverse 101
4.4 Edge AI-empowered Metaverse 102
4.4.1 Cloud-edge-end Empowered Metaverse Network 102
4.4.2 Mobile-edge-cloud Empowered Metaverse Network 103
4.4.3 Decentralized Edge AI Empowered Metaverse Network 104
4.4.4 Personalized and Heterogeneous Edge AI Empowered Metaverse Network 105
4.4.5 Space-Air-Ground Empowered Metaverse Network 106
4.5 AI and Edge AI Empowered Metaverse Applications 107
4.5.1 Telecommuting 107
4.5.2 Immersion Education 108
4.5.3 Smart Cities 108
4.5.4 Industrial Metaverse 109
4.5.5 VR Tourism 109
4.5.6 Digital Virtual Human 109
4.6 Open Research Topics and Future Directions 110
4.6.1 Ownership for AI-Generated Content 110
4.6.2 Deepfakes and User Transparency 110
4.6.3 The Right to be Forgotten 110
4.6.4 Balance Between Virtual and Reality 111
4.6.5 Security 111
4.7 Summary 112
5 How to Secure the Metaverse 113
Zefeng Chen, Jiayi Sun, Jiayang Wu, Wensheng Gan, and Philip S. Yu
5.1 Introduction 113
5.2 Security Issues in the Metaverse 117
5.2.1 Data Collection 118
5.2.1.1 Solutions 119
5.2.2 Data Transmission and Network Communication 119
5.2.2.1 Solutions 121
5.2.3 Data Processing 122
5.2.3.1 Solutions 122
5.2.4 Data Storage and Access 123
5.2.4.1 Solutions 123
5.3 Privacy Issues in the Metaverse 124
5.3.1 Data Collection 125
5.3.1.1 Solutions 125
5.3.2 Data Usage and Access 126
5.3.2.1 Solutions 126
5.3.3 Data Transmission, Storage, and Sharing 127
5.3.3.1 Solutions 127
5.4 Open Problems and Opportunities 128
5.4.1 Security Issues of 5G 128
5.4.2 Security Issues of the Internet of Things 129
5.4.3 Security Issues of Extended Reality Technology 130
5.4.4 Security Issues of Cloud Computing 131
5.5 Summary 132
Bibliography 133
Index 173
List of Contributors xvii
Foreword xix
Preface xxi
1 Introduction 1
Wei Yang Bryan Lim, Zehui Xiong, Dusit Niyato, Junshan Zhang, and Xuemin Sherman Shen
1.1 Introduction 1
1.1.1 Birth of the Metaverse 1
1.2 Architecture, Developments, and Tools of the Metaverse 4
1.2.1 Definition and Architecture 4
1.2.2 Current Developments 9
1.2.2.1 Massive Multiplayer Online Role-playing Games 10
1.2.2.2 Applications of the Metaverse 11
1.2.3 Tools, Platforms, and Frameworks 13
1.2.4 Summary and Lessons Learned 16
1.2.4.1 The Metaverse Cannot Be Realized by a Standalone Technology 16
1.2.4.2 Implementation Challenges 16
1.2.4.3 Standardized Protocols, Frameworks, and Tools 17
1.2.4.4 Metaverse Ecosystem and Economics 17
2 Communication and Computing in Edge-enabled Metaverse 19
Minrui Xu, Wei Chong Ng, Wei Yang Bryan Lim, and Dusit Niyato
2.1 Introduction 19
2.1.1 Rate-Reliability-Latency 3D Multimedia Networks 21
2.1.1.1 Resource Allocation for VR Streaming 25
2.1.1.2 Resource Allocation for AR Adaptation 28
2.1.1.3 Edge Caching for AR/VR Content 30
2.1.1.4 Hologram Streaming 31
2.1.2 Human-in-the-loop Communication 32
2.1.2.1 URLLC for the Tactile Internet 33
2.1.2.2 Semantic/Goal-aware Communication 34
2.1.3 Real-time Physical-Virtual Synchronization 36
2.1.3.1 Resource Allocation for Physical-Virtual Synchronization 37
2.1.3.2 Intelligent Edge Network-aided Virtual-Physical Synchronization 38
2.1.4 Lessons Learned 40
2.1.4.1 Efficient Immersive Streaming and Interaction 40
2.1.4.2 AI for Intelligent Edge Communication 40
2.1.4.3 Context-aware Immersive Content Delivery 40
2.1.4.4 Self-sustainable Physical-Virtual Synchronization 40
2.1.4.5 Decentralized Incentive Mechanism 41
2.2 Computation 41
2.2.1 The Cloud-Edge-End Computing Paradigm 43
2.2.2 Efficient AR/VR Cloud-Edge-End Rendering 45
2.2.2.1 Stochastic Demand and Network Condition 46
2.2.2.2 Stragglers at Edge Networks 48
2.2.2.3 Heterogeneous Tasks 49
2.2.3 Scalable AI Model Training 49
2.2.3.1 Parameter Pruning and Quantization 50
2.2.3.2 Low-rank Approximation 51
2.2.3.3 Knowledge Distillation 52
2.2.4 Privacy and Security 54
2.2.4.1 Trusted Execution Environment 55
2.2.4.2 Federated Learning 56
2.2.4.3 Adversarial Machine Learning 58
2.2.5 Lessons Learned 60
2.2.5.1 Adaptive AR/VR Cloud-Edge-End Rendering 60
2.2.5.2 On-demand and Generalized Model Compression 60
2.2.5.3 User-centric Computing 60
2.2.5.4 Secure Interoperable Computing 61
2.2.5.5 From Distribution to Decentralization 61
2.3 Summary 61
3 Advanced and Future Network Access Technologies for the Metaverse 63
Andrea Garbugli, Domenico Scotece, Luca Foschini, and Paolo Bellavista
3.1 Introduction 63
3.2 Edge-enabled Metaverse 64
3.2.1 Efficient Service Migration at the Edge 65
3.2.1.1 Multi-layer Container Migration 66
3.2.1.2 Metaverse-enabled Service Migration Architecture 68
3.2.1.3 Simulation Results 71
3.3 Ultra-low Latency Communications 73
3.3.1 ULL Networking Protocols 73
3.3.1.1 Time-sensitive Networking (TSN) 74
3.3.1.2 Wireless Networks: 5G and Wi-Fi 6 74
3.3.2 Acceleration Technologies 76
3.3.2.1 Linux eXpress Data Path (XDP) 76
3.3.2.2 Data Plane Development Kit (DPDK) 77
3.3.2.3 Remote Direct Memory Access (RDMA) 77
3.3.2.4 Integration for Metaverse Applications 78
3.3.3 SELENE: A Uniform Acceleration Middleware 78
3.3.3.1 SELENE: The APIs 79
3.3.3.2 SELENE: QoS Policies 81
3.3.3.3 SELENE: The Runtime 82
3.3.3.4 SELENE: Evaluation 85
3.3.3.5 Latency and Throughput Benchmarks 86
3.3.3.6 Lunar Streaming 90
3.4 Summary 92
4 How to Intelligentize the Metaverse 93
Zhe Zhang, Jialin Wu, Ziwen Jin, Xidong Wang, Jiawen Kang, Yanchao Zhao, and Yi Wu
4.1 Seven-layer Model of the Intelligentized Metaverse 93
4.1.1 Experience Layer 93
4.1.2 Exploration and Discovery Layer 94
4.1.3 Creator Economy Layer 95
4.1.4 Spatial Computing Layer 95
4.1.5 Decentralized Layer 95
4.1.6 Human-Computer Interaction Layer 96
4.1.7 Infrastructure Layer 96
4.2 AI for the Metaverse 96
4.2.1 Avatar Creation 96
4.2.2 Empowering 3D Chatbots 97
4.2.3 Language Processing 97
4.2.4 Enabling Human-Computer Interactions 97
4.2.5 3D Scene Rendering 98
4.3 Edge AI for the Metaverse 98
4.3.1 Edge AI Architectures 98
4.3.1.1 Cloud-edge Collaboration Architecture 98
4.3.1.2 Decentralized Architecture 99
4.3.1.3 Federated Learning Architecture 100
4.3.2 How Does Edge AI Contribute to Creating the Metaverse? 100
4.3.2.1 Unique Challenges in the Edge AI-empowered Metaverse 100
4.3.2.2 Benefits of Edge AI for the Metaverse 101
4.4 Edge AI-empowered Metaverse 102
4.4.1 Cloud-edge-end Empowered Metaverse Network 102
4.4.2 Mobile-edge-cloud Empowered Metaverse Network 103
4.4.3 Decentralized Edge AI Empowered Metaverse Network 104
4.4.4 Personalized and Heterogeneous Edge AI Empowered Metaverse Network 105
4.4.5 Space-Air-Ground Empowered Metaverse Network 106
4.5 AI and Edge AI Empowered Metaverse Applications 107
4.5.1 Telecommuting 107
4.5.2 Immersion Education 108
4.5.3 Smart Cities 108
4.5.4 Industrial Metaverse 109
4.5.5 VR Tourism 109
4.5.6 Digital Virtual Human 109
4.6 Open Research Topics and Future Directions 110
4.6.1 Ownership for AI-Generated Content 110
4.6.2 Deepfakes and User Transparency 110
4.6.3 The Right to be Forgotten 110
4.6.4 Balance Between Virtual and Reality 111
4.6.5 Security 111
4.7 Summary 112
5 How to Secure the Metaverse 113
Zefeng Chen, Jiayi Sun, Jiayang Wu, Wensheng Gan, and Philip S. Yu
5.1 Introduction 113
5.2 Security Issues in the Metaverse 117
5.2.1 Data Collection 118
5.2.1.1 Solutions 119
5.2.2 Data Transmission and Network Communication 119
5.2.2.1 Solutions 121
5.2.3 Data Processing 122
5.2.3.1 Solutions 122
5.2.4 Data Storage and Access 123
5.2.4.1 Solutions 123
5.3 Privacy Issues in the Metaverse 124
5.3.1 Data Collection 125
5.3.1.1 Solutions 125
5.3.2 Data Usage and Access 126
5.3.2.1 Solutions 126
5.3.3 Data Transmission, Storage, and Sharing 127
5.3.3.1 Solutions 127
5.4 Open Problems and Opportunities 128
5.4.1 Security Issues of 5G 128
5.4.2 Security Issues of the Internet of Things 129
5.4.3 Security Issues of Extended Reality Technology 130
5.4.4 Security Issues of Cloud Computing 131
5.5 Summary 132
Bibliography 133
Index 173