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2.Edge Computing Architecture and Layers | 2.Edge Computing Architecture and Layers | ||
2.1 IoT, Mobile, and Digital Twins | 2.1 IoT, Mobile, and Digital Twins | ||
2.2 Cloud | 2.2 Cloud | ||
2.3 Edge and Fog | 2.3 Edge and Fog | ||
2.4 Edge-Cloud Continuum | 2.4 Edge-Cloud Continuum | ||
3.Edge Computing Products and Frameworks | 3.Edge Computing Products and Frameworks | ||
3.1 Industry Products: AWS as an Example | 3.1 Industry Products: AWS as an Example | ||
3.2 Open Source Frameworks | 3.2 Open Source Frameworks | ||
3.3 Serverless at the Edge | 3.3 Serverless at the Edge | ||
4.Machine Learning at the Edge | 4.Machine Learning at the Edge | ||
4.1 Overview of ML at the Edge | 4.1 Overview of ML at the Edge | ||
4.2 ML Training at the Edge | 4.2 ML Training at the Edge | ||
4.3 ML Model Optimization for the Edge | 4.3 ML Model Optimization for the Edge | ||
4.4 Federated Learning | 4.4 Federated Learning | ||
5.Edge Security and Privacy | 5.Edge Security and Privacy | ||
5.1 Overview of Security Challenges in Edge Computing | 5.1 Overview of Security Challenges in Edge Computing | ||
5.2 Data Privacy and Compliance in Edge Applications | 5.2 Data Privacy and Compliance in Edge Applications | ||
5.3 Security Protocols and Frameworks for Edge Systems | 5.3 Security Protocols and Frameworks for Edge Systems | ||
5.4 Case Studies: Real-World Security Breaches | 5.4 Case Studies: Real-World Security Breaches | ||
6. Emerging Research Directions | 6. Emerging Research Directions | ||
6.1 Task and Resource Scheduling | 6.1 Task and Resource Scheduling | ||
6.2 Edge for AR/VR | 6.2 Edge for AR/VR | ||
6.3 Vehicle Computing | 6.3 Vehicle Computing | ||
6.4 Energy-Efficient Edge Architectures | 6.4 Energy-Efficient Edge Architectures | ||
7.Conclusion and Future Outlook (cannot be chosen by students) | 7.Conclusion and Future Outlook (cannot be chosen by students) | ||
Revision as of 23:14, 22 January 2025
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Structure of this WiKi
1.Introduction
1.1 What is Edge Computing
1.2 Why We Need Edge Computing
1.3 Edge Computing Application Domains and Typical Applications
1.4 Different Edge Computing Paradigms (include Cloud-Edge Continuum here)
2.Edge Computing Architecture and Layers
2.1 IoT, Mobile, and Digital Twins
2.2 Cloud
2.3 Edge and Fog
2.4 Edge-Cloud Continuum
3.Edge Computing Products and Frameworks
3.1 Industry Products: AWS as an Example
3.2 Open Source Frameworks
3.3 Serverless at the Edge
4.Machine Learning at the Edge
4.1 Overview of ML at the Edge
4.2 ML Training at the Edge
4.3 ML Model Optimization for the Edge
4.4 Federated Learning
5.Edge Security and Privacy
5.1 Overview of Security Challenges in Edge Computing
5.2 Data Privacy and Compliance in Edge Applications
5.3 Security Protocols and Frameworks for Edge Systems
5.4 Case Studies: Real-World Security Breaches
6. Emerging Research Directions
6.1 Task and Resource Scheduling
6.2 Edge for AR/VR
6.3 Vehicle Computing
6.4 Energy-Efficient Edge Architectures
7.Conclusion and Future Outlook (cannot be chosen by students)