325  Edge, Fog, and Cloud: Architecture

325.1 Learning Objectives

By the end of this chapter, you will be able to:

  • Understand Alternative Terminologies: Recognize MGC (eMbedded-Gateway-Cloud) architecture naming
  • Explain the Three-Layer Architecture: Describe Edge, Fog, and Cloud nodes in detail
  • Compare Device Types: Differentiate between edge nodes, fog nodes, and cloud nodes
  • Design Protocol Translation: Plan data conversion across architecture layers

325.2 Prerequisites

Before diving into this chapter, you should have completed:

325.3 Key Concepts

  • Three-Layer Architecture: IoT systems are organized into Edge Nodes (sensors/devices), Fog Nodes (gateways/intermediate processing), and Cloud Nodes (data centers for large-scale analytics and storage)
  • Seven-Level IoT Reference Model: Cisco’s structured framework defining layers from physical devices through connectivity, edge computing, storage, abstraction, applications, to collaboration and processes
  • Edge Nodes: Physical devices and sensors that collect data from the environment, including microcontrollers, embedded devices, and smart appliances
  • Fog Nodes: Intermediate processing layer using single-board computers and gateways to filter data and reduce cloud bandwidth requirements
  • Cloud Nodes: Centralized data centers providing extensive computational resources for machine learning, analytics, and device management
  • Protocol Translation: Converting data between different communication protocols (Bluetooth, Zigbee, MQTT, HTTP) as it flows through the architecture layers
TipAlternative Terminology: MGC Architecture

You may encounter the three-tier architecture described as MGC (eMbedded–Gateway–Cloud). The following diagram from Stanford’s IoT course illustrates this hierarchical architecture:

Three-tier MGC architecture showing the hierarchical organization of IoT systems from embedded devices through gateways to cloud infrastructure, with clear delineation of processing responsibilities at each tier.

Figure 325.1

The diagram shows how embedded devices (sensors, wearables, appliances) connect to gateways (smartphones, vehicles, hubs) which bridge to cloud services (storage, analytics, ML/AI). Each tier has distinct characteristics:

Graph diagram

Graph diagram
Figure 325.2: Three-tier IoT architecture showing embedded devices on left connected via 6LoWPAN, Zigbee, Z-Wave, Bluetooth, Wi-Fi, or WirelessHART to gateways in…
This Chapter MGC Terminology Description
Edge eMbedded Sensors, wearables, smart appliances with constrained resources
Fog Gateway Smartphones, vehicles, hubs that bridge protocols and aggregate data
Cloud Cloud Data centers for storage, analytics, and ML training

The MGC terminology emphasizes the role of each tier rather than its location, making it useful when discussing protocol translation (embedded devices speak different languages than cloud services) and data aggregation patterns.

325.3.1 MGC Architecture with Protocol Details

The following figure from Stanford’s IoT course provides a detailed view of the MGC architecture showing specific devices and communication protocols at each tier:

MGC architecture with detailed device and protocol mapping across tiers: Embedded layer shows specific sensors (temperature, motion, GPS) and MCUs (Arduino, ESP32), Gateway layer illustrates protocol bridging (Zigbee→MQTT, BLE→HTTP), and Cloud layer displays platform services (AWS IoT Core, Azure IoT Hub, ThingSpeak) for storage and analytics.

Figure 325.3

This detailed architecture view illustrates how different IoT protocols and devices map to the three-tier MGC model. At the embedded tier, constrained devices use low-power protocols (Zigbee, BLE, LoRa) optimized for battery operation. The gateway tier performs critical protocol translation—converting Zigbee packets to MQTT messages, BLE advertisements to HTTP REST calls, and LoRaWAN frames to JSON payloads. Finally, the cloud tier receives standardized data formats (typically MQTT or HTTP) that platform services can process uniformly regardless of the original embedded protocol.

Key Protocol Translation Examples:

Embedded Protocol Gateway Translation Cloud Protocol Use Case
Zigbee (802.15.4) Zigbee2MQTT gateway MQTT over TCP Smart home sensors (battery-powered, mesh network)
BLE Advertisements BLE-HTTP bridge HTTP REST API Asset tracking beacons (periodic broadcasts)
LoRaWAN Network server JSON/HTTP webhook Agricultural sensors (long-range, low data rate)
Modbus RTU Modbus-TCP gateway MQTT/OPC-UA Industrial PLCs (wired serial to IP networks)

This architecture enables heterogeneous device integration—your cloud application receives uniform MQTT messages regardless of whether data originated from Zigbee sensors, BLE beacons, or LoRaWAN nodes.

Artistic visualization of the edge-fog-cloud computing continuum showing IoT devices at the edge generating data, fog nodes in the middle performing local processing and aggregation, and cloud data centers at the top providing massive compute and storage, with data flowing upward and control signals flowing downward through the layers

Edge-Fog-Cloud continuum visualization
Figure 325.4: The edge-fog-cloud continuum represents a spectrum of computing resources with varying characteristics. Rather than discrete layers, modern IoT architectures treat this as a continuous range where workloads can be placed optimally based on latency, bandwidth, privacy, and reliability requirements. The challenge is determining where to process each type of data for the best overall system performance.

Geometric diagram of three-tier IoT architecture with edge layer at bottom containing sensors and actuators, fog layer in middle with gateways and local servers, and cloud layer at top with data centers, showing data aggregation flowing upward and commands flowing downward through protocol translation points

Three-tier IoT architecture
Figure 325.5: The three-tier architecture organizes IoT systems into distinct processing layers. Edge devices collect raw sensor data and execute immediate control actions. Fog nodes aggregate data from multiple edge devices, perform filtering and local analytics, and translate between edge protocols and cloud-compatible formats. Cloud systems provide unlimited storage, historical analytics, and cross-site coordination.

325.4 Edge, Fog, and Cloud

⏱️ ~12 min | ⭐⭐ Intermediate | 📋 P05.C04.U02

The architecture of IoT systems is typically organized into three main layers: Edge Nodes, Fog Nodes, and Cloud Nodes. Each layer plays a crucial role in the overall functionality and efficiency of the IoT system. Below, we discuss these components in detail, supported by visual representations from the slides.

Two-panel diagram showing mobile cloud computing architecture at top with mobile network services, gateways, internet backbone, and cloud data centers, plus device growth projection chart at bottom showing billions of devices from 2014-2019 with category breakdown

Mobile cloud computing architecture showing mobile network services connecting through the internet to cloud computing infrastructure. The diagram illustrates how mobile devices connect through local network gateways to reach cloud services, with a chart showing device growth from 2014-2019 projecting 9% CAGR reaching over 12 billion devices. The chart breaks down device categories: smartphones (57%, 40%), M2M (13%, 60%), tablets (4%, 4%), laptops (4%, 2%), and other portable devices (2.3%, 0.6%).

Source: Princeton University, Coursera Fog Networks for IoT (Prof. Mung Chiang)

Modern visualization of the edge-fog-cloud computing continuum showing a layered architecture with IoT devices and sensors at the edge layer, fog nodes and gateways in the middle tier providing local processing and aggregation, and cloud data centers at the top for large-scale analytics and storage, with bidirectional data flow arrows indicating real-time and batch processing paths

Edge-Fog-Cloud Continuum Architecture
Figure 325.6: The edge-fog-cloud continuum provides a hierarchical processing architecture where computation is distributed based on latency requirements, bandwidth constraints, and processing complexity. Edge nodes handle immediate responses, fog nodes aggregate and filter data, while cloud performs long-term analytics and ML training.

Artistic comparison of the three computing tiers in IoT architecture showing edge tier characteristics (millisecond latency, limited compute, battery-powered), fog tier properties (second-range latency, moderate compute, local storage), and cloud tier capabilities (minute-range latency, unlimited compute, massive storage), with example devices and use cases for each tier

Edge-Fog-Cloud Tier Comparison
Figure 325.7: Comparison of edge, fog, and cloud computing tiers highlighting the tradeoffs between latency, compute power, and storage capacity at each level of the IoT architecture hierarchy.
TipUnderstanding Device Management at Scale

Core Concept: Device management encompasses the lifecycle operations of IoT devices - provisioning, configuration, monitoring, firmware updates, and decommissioning - across potentially thousands of geographically distributed endpoints.

Why It Matters: A factory with 500 sensors or a retail chain with 10,000 devices cannot manage each unit manually. Without automated device management, organizations face unpatched security vulnerabilities, inconsistent configurations, and operational blind spots. The fog layer typically hosts device management agents that aggregate status from edge devices and relay commands from cloud platforms, enabling centralized control with local execution.

Key Takeaway: Design for zero-touch provisioning from day one - devices should self-register with fog gateways using secure bootstrapping (certificates, TPM), receive their configuration automatically, and report health metrics without manual intervention.

325.4.1 Edge Nodes

Edge Nodes are the physical devices or sensors that collect data from the environment. They are the first point of interaction with the physical world and are responsible for data acquisition.

  • Micro-Controller Based Edge Nodes: These include devices such as the Intel Edison, Arduino boards, and other microcontroller units (MCUs) that perform simple processing tasks at the edge.
  • Embedded Devices: Common examples include smart appliances like refrigerators, smart locks, and wearable devices like smartwatches. These devices are embedded with sensors and connectivity modules to gather and transmit data.

Examples of Edge Nodes: - Intel Edison: A compact computing platform designed for building IoT projects. - Arduino: A popular open-source electronics platform based on easy-to-use hardware and software. - Smart Appliances: Refrigerators, smart locks, and smart lighting systems that collect and transmit data to other IoT components.

Artistic representation of an IoT edge node showing internal components including microcontroller unit, sensor interfaces, communication modules (Wi-Fi, BLE, LoRa), power management circuitry, and local storage, with arrows indicating sensor data input and network data output

Edge Node Architecture
Figure 325.8: Internal architecture of a typical IoT edge node showing the integration of sensing, processing, communication, and power management components that enable autonomous data collection and transmission.

Edge gateway device visualization showing multiple communication interfaces (Ethernet, Wi-Fi, Zigbee, BLE) for connecting to diverse IoT devices, local processing capability for data filtering and aggregation, and uplink connectivity to cloud services via cellular or broadband

Edge Gateway Architecture
Figure 325.9: Edge gateway architecture illustrating the role of gateway devices in bridging heterogeneous IoT protocols and providing local intelligence before forwarding processed data to cloud infrastructure.

Geometric diagram showing the key functions performed by edge gateways including protocol translation, data aggregation, local analytics, security enforcement, device management, and cloud connectivity, with data flow arrows between functional blocks

Edge Gateway Functions
Figure 325.10: Key functions of edge gateways in IoT architectures: protocol translation enables diverse device connectivity, data aggregation reduces bandwidth, local analytics support real-time decisions, and security enforcement protects the network perimeter.

325.4.2 Fog Nodes

Fog Nodes act as intermediaries between edge devices and the cloud. They perform intermediate processing, data filtering, and storage to reduce the data volume sent to the cloud and to improve response times.

  • Single Board Computers: These include devices like Raspberry Pi and BeagleBone that can handle more complex processing tasks compared to simple microcontrollers.
  • Gateways: Devices that aggregate data from multiple edge nodes and provide a secure pathway to transmit data to the cloud. They often support various communication protocols such as 6LoWPAN, Zigbee, Z-Wave, Bluetooth, Wi-Fi, and WirelessHART.

Examples of Fog Nodes: - Raspberry Pi: A versatile single-board computer that can act as a fog node, performing local data processing and analytics. - BeagleBone: Another single-board computer used for IoT applications requiring more processing power. - Gateways: Devices that bridge communication between edge nodes and the cloud, ensuring efficient data transfer and processing.

325.4.3 Cloud Nodes

Cloud Nodes represent the data centers or cloud platforms that provide extensive computational resources for large-scale data processing, storage, and analytics. They form the backbone of IoT systems, offering services such as machine learning, data visualization, and device management.

  • Cloud Data Centers: These include platforms like Amazon Web Services (AWS), Microsoft Azure IoT Suite, IBM Bluemix, and Kaa IoT Platform.
  • Services: Cloud platforms offer various services including data analytics, storage, device management, and application hosting.

Examples of Cloud Nodes: - Amazon Web Services (AWS): Provides a comprehensive suite of IoT services for building scalable IoT applications. - Microsoft Azure IoT Suite: Offers tools and services for connecting, monitoring, and controlling IoT assets. - IBM Bluemix: A cloud platform that helps in developing, managing, and running IoT applications.

325.4.4 Integration of Architectural Components

The integration of edge, fog, and cloud nodes creates a seamless and efficient IoT architecture. Data collected from edge devices are pre-processed at fog nodes to reduce latency and bandwidth usage before being transmitted to cloud nodes for further analysis and storage. This layered architecture enhances the performance, scalability, and reliability of IoT systems.

Understanding the architectural components of IoT systems is essential for designing efficient and effective IoT solutions. By leveraging the strengths of edge, fog, and cloud nodes, IoT systems can achieve optimal performance and scalability, catering to a wide range of applications from smart homes to industrial IoT.

This section provides a detailed overview of the architectural components of IoT systems, supported by examples and visual aids from the provided slides, making it suitable for inclusion in a textbook or educational material on IoT.

325.5 What’s Next

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