This is an open access book.<div><br></div><div><div>It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks.</div><div>The book starts with
Mobile Edge Computing
β Scribed by Yan Zhang
- Publisher
- Springer
- Year
- 2021
- Tongue
- English
- Leaves
- 123
- Series
- Simula SpringerBriefs on Computing
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This is an open access book.
β¦ Table of Contents
Preface
Acknowledgements
Contents
Acronyms
1 Introduction
1.1 Mobile Cloud Computing (MCC)
1.2 Overview of MEC
1.3 Book Organization
2 Mobile Edge Computing
2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC)
2.2 Computation Model
2.2.1 Computation Model of Local Execution
2.2.2 Computation Model of Full Offloading
2.2.3 A Computation Model for Partial Offloading
2.3 Offloading Policy
2.3.1 Binary Offloading
2.3.2 Partial Offloading
2.4 Challenges and Future Directions
3 Mobile Edge Caching
3.1 Introduction
3.2 The Architecture of Mobile Edge Caching
3.3 Caching Performance Metrics
3.3.1 Hit Rate Ratio
3.3.2 Content Acquisition Latency
3.3.3 Quality of Experience (QoE)
3.3.4 Caching System Utility
3.4 Caching Service Design and Data Scheduling Mechanisms
3.4.1 Edge Caching Based on Network Infrastructure Services
3.4.2 Edge Caching Based on D2D Services
3.4.3 Hybrid ServiceβEnabled Edge Caching
3.5 Case Study: Deep Reinforcement LearningβEmpowered β¦
3.5.1 System Model
3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme
3.5.3 Numerical Results
4 Mobile Edge Computing for Beyond 5G/6G
4.1 Fundamental Characteristics of 6G
4.2 Integrating Mobile Edge Computing (MEC) β¦
4.2.1 Use Cases of Integrating MEC into 6G
4.2.2 Applications of Integrating MEC into 6G
4.2.3 Challenges of Integrating MEC into 6G
4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G
4.3.1 Sharing at the Edge: From Data to Model
4.3.2 Architecture of Edge Model Sharing
4.3.3 Processes of Edge Model Sharing
5 Mobile Edge Computing for the Internet of Vehicles
5.1 Introduction
5.2 Challenges in VEC
5.3 Architecture of VEC
5.4 Key Techniques of VEC
5.4.1 Task Offloading
5.4.2 Heterogeneous Edge Server Cooperation
5.4.3 AI-Empowered VEC
5.5 A Case Study
5.5.1 Predictive Task Offloading for Fast-Moving Vehicles
5.5.2 Deep Q-Learning for Vehicular Computation Offloading
6 Mobile Edge Computing for UAVs
6.1 Unmanned Aerial VehicleβAssisted Mobile Edge Computing (MEC) Networks
6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks
6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities
6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server
6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading
6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm
6.3.1 UAV Deployment for MEC at a Wind Farm
6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm
6.4 Conclusions
7 The Future of Mobile Edge Computing
7.1 The Integration of Blockchain and Mobile Edge Computing (MEC)
7.1.1 The Blockchain Structure
7.1.2 Blockchain Classification
7.1.3 Integration of Blockchain and MEC
7.2 Edge Intelligence: The Convergence of AI and MEC
7.2.1 Federated Learning in MEC
7.2.2 Transfer Learning in MEC
7.3 MEC in Other Applications
7.3.1 MEC in Pandemics
7.3.2 MEC in the Industrial IoT (IIoT)
7.3.3 MEC in Disaster Management
Appendix References
π SIMILAR VOLUMES
<div>Mobile Edge Computing (MEC) provides cloud-like subscription-oriented services at the edge of mobile network. For low latency and high bandwidth services, edge computing assisted IoT (Internet of Things) has become the pillar for the development of smart environments and their applications such
<div>Mobile Edge Computing (MEC) provides cloud-like subscription-oriented services at the edge of mobile network. For low latency and high bandwidth services, edge computing assisted IoT (Internet of Things) has become the pillar for the development of smart environments and their applications such
<span>This book provides a comprehensive review and in-depth discussion of the state-of-the-art research literature and propose energy-efficient computation offloading and resources management for mobile edge computing (MEC), covering task offloading, channel allocation, frequency scaling and resour