Description
Book SynopsisChapter 1: Introduction to Cloud, Fog, and Edge Computing in Healthcare.- Chapter 2: Addressing the Challenges in Federating Edge Resources.- Chapter 3: Integrating IoT + Fog + Cloud Infrastructures: System Modelling and Research Challenges.- Chapter 4: Blockchain and Federated Learning for the Management and Orchestration of Network Slices in 5G, Fog, Edge, and Clouds.- Chapter 5: Health Optimization Problems in Fog and Edge Computing with Machine Learning.- Chapter 6: A Lightweight AI-Enabled Container Middleware for Edge Cloud Architectures.- Chapter 7: Health Data Management in Fog Computing using Machine Learning.- Chapter 8: Predictive Analysis in Healthcare to Support Fog Application Deployment.- Chapter 9: Using Machine Learning for Protecting the Security and Privacy of Internet of Medical Things (IoMT) Systems.- Chapter 10: Fog Computing Realization for Healthcare-Based Big Data Analytics with Machine Learning.- Chapter 11: Exploiting Fog Computing and Federated Learning in Health Monitoring.- Chapter 12: Smart Surveillance Video Stream Processing at the Edge for Real-Time Patient Activity Tracking with Machine Learning.- Chapter 13: Fog Computing Model for Evolving Smart Healthcare Applications.- Chapter 14: Testing Perspectives of Fog-Based IoMT Applications with Federated Learning.- Chapter 15: Legal Aspects of Operating IoMT Applications in the Fog Computing.
