Edge Computing and Fog Computing
Description
Understanding edge computing architectures and implementation for IoT applications
Learning Objectives
Learners will master edge computing concepts, architectures, and implementation strategies for IoT systems. They will understand the benefits of edge processing, fog computing models, deployment strategies, and be able to design hybrid cloud-edge architectures for latency-sensitive and bandwidth-constrained IoT applications.
Topics (7)
Introduction to edge computing including definitions, use cases, and comparison with cloud computing
Hardware and software considerations for edge devices including processing capabilities and connectivity
Fog computing concepts including hierarchical processing and distributed intelligence
Deployment of AI models on edge devices including optimization and inference techniques
Container technologies for edge deployment including lightweight orchestration solutions
Security challenges and solutions specific to edge computing including device security and data protection
Integration strategies for cloud-edge hybrid systems including data flow and workload distribution