314  Edge and Fog Computing

Prerequisites: Cloud Computing | IoT Reference Architectures

This enables: Edge AI/ML | Edge Compute Patterns

314.1 Overview

Edge and fog computing extend cloud capabilities to the network edge, enabling real-time processing, bandwidth optimization, and resilient IoT systems. This comprehensive chapter series covers the fundamental concepts, architecture patterns, practical use cases, and hands-on implementation of distributed computing for IoT.

Why Edge and Fog Computing Matters:

  • Latency: Cloud round-trips take 100-300ms; edge processing achieves 5-15ms
  • Bandwidth: Edge filtering reduces data transmission by 90-99%
  • Reliability: Local processing continues during network outages
  • Privacy: Sensitive data processed locally, never leaves the premises
  • Cost: Reduces cloud bandwidth and processing costs by orders of magnitude

314.2 Chapter Series

This topic is covered in 11 focused chapters:

314.2.1 Foundations

  1. Introduction - Core concepts, definitions, and business value
    • What is edge and fog computing?
    • Key terminology and concepts
    • Executive summary for business leaders
    • Sensor Squad kids section
  2. The Latency Problem - Why milliseconds matter
    • Physics of network latency
    • Speed of light constraints
    • Safety-critical application requirements
    • Self-driving car calculations
  3. Bandwidth Optimization - Cost calculations and data reduction
    • IoT data volume calculations
    • Cloud-only vs edge/fog cost comparison
    • ROI analysis for edge infrastructure
    • Data gravity principle

314.2.2 Architecture and Design

  1. Decision Framework - When to use edge vs fog vs cloud
    • Decision tree for architecture selection
    • Detailed criteria for each tier
    • Cost-benefit analysis framework
    • Four architecture patterns
  2. Architecture - Three-tier design and fog node capabilities
    • Three-tier architecture (Edge, Fog, Cloud)
    • Fog node capabilities
    • Data flow and processing pipelines
    • GigaSight framework case study
  3. Advantages and Challenges - Benefits and implementation challenges
    • Performance, operational, and security advantages
    • Resource constraints and management complexity
    • Energy-latency trade-offs
    • Network topology considerations

314.2.3 Interactive Learning

  1. Interactive Simulator - Hands-on latency visualization tool
    • Adjust data size, complexity, distance
    • Compare edge, fog, and cloud latency
    • Real-world scenario presets
    • Bandwidth cost calculator

314.2.4 Applications

  1. Use Cases - Factory, vehicle, and privacy applications
    • Smart factory predictive maintenance
    • Autonomous vehicle edge computing
    • Privacy-preserving architecture
    • Agricultural drone worked example

314.2.5 Implementation

  1. Common Pitfalls - Mistakes to avoid
    • Retry logic without backoff
    • Missing local buffering
    • Device management neglect
    • Clock synchronization issues
  2. Hands-On Labs - Wokwi ESP32 simulation exercises
    • Edge vs cloud latency comparison
    • Data aggregation implementation
    • Hybrid architecture design
    • Challenge exercises

314.3 Quick Reference

314.3.1 Key Metrics

Tier Typical Latency Best For Bandwidth Impact
Edge 1-10 ms Safety-critical, real-time control 99%+ reduction (only events)
Fog 10-100 ms Multi-device coordination, local analytics 90-99% reduction
Cloud 100-300 ms ML training, global analytics, storage Full data (if needed)

314.3.2 When to Use Each Tier

Requirement Recommendation
Latency < 10ms Edge (mandatory)
Latency < 100ms Fog (preferred)
Latency > 200ms OK Cloud (acceptable)
Must work offline Edge/Fog
Privacy regulations Edge/Fog
Massive compute needed Cloud
10,000+ devices Hierarchical Fog

314.3.3 Cost Comparison (1,000 sensor factory example)

Architecture Monthly Cost Annual Cost
Cloud-only $106,354 $1,276,248
Edge + Fog $2,526 $30,312
Savings 98% $1,245,936/year

314.4 Learning Path

Recommended order for first-time learners:

  1. Start with Introduction for foundational concepts
  2. Understand the physics in The Latency Problem
  3. Learn about costs in Bandwidth Optimization
  4. Use the Decision Framework to choose architectures
  5. Study the Architecture details
  6. Explore the Interactive Simulator
  7. Review Use Cases for practical applications
  8. Complete the Hands-On Labs

For experienced practitioners:

314.5 What’s Next?

Start your journey through edge and fog computing:

Begin with Introduction –>

Or explore related topics: