Mobile edge computing

• Published in: Simula SpringerBriefs on computing Vol. 9
• Main Author: Zhang, Yan
• Format: eBook Book
• Language: English
• Published: Cham, Switzerland Springer 2022; Springer Nature; Springer International Publishing AG; Simula Research Laboratory
• Edition: 1
• Series: Simula SpringerBriefs on Computing
• Subjects: 5G beyond; Artificial intelligence > Data processing; Communications engineering / telecommunications; Computer programming / software engineering; Computer Technology; Computing and Information Technology; edge caching; Edge computing; Electrical engineering; Electronics and communications engineering; Energy technology and engineering; Engineering; Internet of Things; Machine learning; Mobile and handheld device programming / Apps programming; Mobile apps; mobile edge computing; Nonfiction; Open Access; Technology; Technology, Engineering, Agriculture, Industrial processes; UAV; WAP (wireless) technology
• ISBN: 3030839435; 9783030839437; 3030839443; 9783030839444
• ISSN: 2512-1677; 2512-1685
• DOI: 10.1007/978-3-030-83944-4

This is an open access book. 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. The book starts with the basic concepts, key technique...

Table of Contents:

• Intro -- 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 Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 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) … -- 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 Vehicle-Assisted 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