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Fog Computing
Читать книгу Fog Computing - Группа авторов - Страница 1
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Страница 1
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
WILEY SERIES ON PARALLEL AND DISTRIBUTED COMPUTING
Fog Computing: Theory and Practice
Страница 9
Страница 10
1 Mobile Fog Computing
1.1 Introduction
1.2 Mobile Fog Computing and Related Models
1.3 The Needs of Mobile Fog Computing
1.3.1 Infrastructural Mobile Fog Computing 1.3.1.1 Road Crash Avoidance
1.3.1.2 Marine Data Acquisition
1.3.1.3 Forest Fire Detection
1.3.1.4 Mobile Ambient Assisted Living
1.3.2 Land Vehicular Fog
1.3.3 Marine Fog
1.3.4 Unmanned Aerial Vehicular Fog
1.3.5 User Equipment-Based Fog
1.3.5.1 Healthcare
1.3.5.2 Content Delivery
1.3.5.3 Crowd Sensing
1.4 Communication Technologies
1.4.1 IEEE 802.11
1.4.2 4G, 5G Standards
1.4.3 WPAN, Short-Range Technologies
1.4.4 LPWAN, Other Medium- and Long-Range Technologies
1.5 Nonfunctional Requirements
1.5.1 Heterogeneity
1.5.1.1 Server Heterogeneity
1.5.1.2 End-Device Heterogeneity
1.5.1.3 End-to-End Network Heterogeneity
1.5.2 Context-Awareness
1.5.2.1 Server Context
1.5.2.2 Mobility Context
1.5.2.3 End-to-end Context
1.5.2.4 Application Context
1.5.3 Tenant
1.5.3.1 Application Management
1.5.3.2 Cost of Energy and Tenancy
1.5.4 Provider
1.5.4.1 Physical Placement
1.5.4.2 Server Discoverability and Connectivity
1.5.4.3 Operation Management
1.5.4.4 Operation Cost
1.5.5 Security
1.5.5.1 Physical Security
1.5.5.2 End-to-End Security
1.5.5.3 Security Monitoring and Management
1.5.5.4 Trust Management and Multitenancy Security
1.6 Open Challenges
1.6.1 Challenges in Land Vehicular Fog Computing
1.6.2 Challenges in Marine Fog Computing
1.6.3 Challenges in Unmanned Aerial Vehicular Fog Computing
1.6.4 Challenges in User Equipment-based Fog Computing
1.6.5 General Challenges 1.6.5.1 Testbed Tool
1.6.5.2 Autonomous Runtime Adjustment and Rapid Redeployment
1.6.5.3 Scheduling of Fog Applications
1.6.5.4 Scalable Resource Management of Fog Providers
1.7 Conclusion
Acknowledgment
References
Note
2 Edge and Fog: A Survey, Use Cases, and Future Challenges
2.1 Introduction
2.2 Edge Computing
2.2.1 Edge Computing Architecture
2.3 Fog Computing
2.3.1 Fog Computing Architecture
2.4 Fog and Edge Illustrative Use Cases
2.4.1 Edge Computing Use Cases
2.4.1.1 A Wearable ECG Sensor
2.4.1.2 Smart Home
2.4.2 Fog Computing Use Cases
2.4.2.1 Smart Traffic Light System
2.4.2.2 Smart Pipeline Monitoring System
2.5 Future Challenges
2.5.1 Resource Management
2.5.2 Security and Privacy
2.5.3 Network Management
2.6 Conclusion
Acknowledgment
References
3 Deep Learning in the Era of Edge Computing: Challenges and Opportunities
3.1 Introduction
3.2 Challenges and Opportunities 3.2.1 Memory and Computational Expensiveness of DNN Models
3.2.2 Data Discrepancy in Real-world Settings
3.2.3 Constrained Battery Life of Edge Devices
3.2.4 Heterogeneity in Sensor Data
3.2.5 Heterogeneity in Computing Units
3.2.6 Multitenancy of Deep Learning Tasks
3.2.7 Offloading to Nearby Edges
3.2.8 On-device Training
3.3 Concluding Remarks
References
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