دانلود کتاب Digital Twin: Architectures, Networks, and Applications (Simula SpringerBriefs on Computing, 16)

فهرست مطالب :

Series Foreword
Preface
Acknowledgements
Contents
Acronyms
Chapter 1 Introduction
1.1 Overview of Digital Twin
1.2 Digital Twin Concepts, Features, and Visions
1.3 Book Organization
Chapter 2 Digital Twin Models and Networks
2.1 Digital Twin Models
2.1.1 DT Modelling Methods
2.1.2 DT Modelling Challenges
2.2 DT Networks (DTNs)
2.2.1 DTN Concepts
2.2.2 DTN Communications
2.2.3 DTN Applications
2.2.4 Open DTN Research Issues
Chapter 3 Artificial Intelligence for Digital Twin
3.1 Artificial Intelligence in Digital Twin
3.2 DRL-Empowered DT
3.2.1 Introduction to DRL
3.2.2 Incorporation of DT and DRL
3.2.3 Open Research Issues
3.3 Federated Learning (FL) for DT
3.3.1 Introduction to FL
3.3.2 Incorporation of DT and FL
3.3.3 Open Research Issues
3.4 Transfer Learning (TL) for DT
3.4.1 Introduction to TL
3.4.2 Incorporation of DT and TL
3.4.3 Open Research Issues
Chapter 4 Edge Computing for Digital Twin
4.1 Digital Twin Edge Networks
4.1.1 Digital Twin Edge Network Architecture
4.1.2 Computation Offloading in Digital Twin Edge Networks
4.2 AI for Digital Twin Edge Networks
4.2.1 System Model
4.2.2 Communication and Computation Model
4.2.3 Latency Model
4.3 Edge Association for Digital Twin Edge Networks
4.3.1 System Model
4.3.2 Edge Association: Definition and Problem Formulation
4.3.3 Multi-Agent DRL for Edge Association
Chapter 5 Blockchain for Digital Twin
5.1 Blockchain-Empowered Digital Twin
5.2 Block Generation and Consensus for Digital Twin
5.2.1 Blockchain Model
5.2.2 Relay-Assisted Transaction Relaying Scheme
5.2.3 DPoS-Based Lightweight Block Verification Scheme
5.2.4 Conclusion
Chapter 6 Digital Twin for 6G Networks
6.1 Integration of Digital Twin and Sixth-Generation (6G) Networks
6.2 Potential Use Cases
6.3 Digital Twin for RIS
6.3.1 System Model
6.3.2 Computation Offloading in Digital Twin–Aided RIS
6.4 Stochastic Computation Offloading
6.4.1 System Model
6.4.2 Stochastic Computation Offloading: Definition and Problem Formulation
6.4.3 Lyapunov Optimization for Stochastic Computation Offloading
Chapter 7 Digital Twin for Aerial-Ground Networks
7.1 Introduction
7.2 Key Techniques
7.2.1 Cross-Domain Resource Management
7.2.2 Cross-Device Intelligent Cooperation
7.3 DT for Task Offloading in Aerial-Ground Networks
7.3.1 System Model
7.3.2 Utility Function
7.3.3 Distributed Incentives for Satisfaction and Energy Efficiency Maximization
7.3.4 Illustration of the Results
7.4 DT and Federated Learning for Aerial-Ground Networks
7.4.1 A DT Drone-Assisted Ground Network Model
7.4.2 Contribution Measurement and Reputation Value Model
7.4.3 Incentive for Federated Learning Utility Maximization
7.4.4 Illustration of the Results
Chapter 8 Digital Twin for the Internet of Vehicles
8.1 Introduction
8.2 DT for Vehicular Edge Computing
8.2.1 System Model
8.2.2 DT and Multi-Agent Deep Reinforcement Learning for VEC
8.2.3 Illustrative Results
8.3 DT for Vehicular Edge Caching
8.3.1 System Model
8.3.2 DT-Empowered Content Caching
8.3.3 Illustrative Results
References