IIoT Architecture: Edge, Fog, and Cloud — Choosing the Right Topology
Industrial IoT architecture decisions made early have long-term consequences for latency, cost, and scalability. Here's a practical framework for making the right call.
The Architecture Decision That Matters Most
When designing an IIoT system, no decision has more long-term consequence than where to process data: at the edge, in a fog layer, or in the cloud.
Edge Computing: Process at the Source
Edge computing processes data on or near the machine. Choose edge when you need sub-10ms response times for control decisions, when connectivity is unreliable or expensive, or when data sovereignty requires local processing.
Fog Computing: The Middle Layer
Fog computing adds a processing layer between edge devices and the cloud. Fog is ideal for aggregation across multiple machines, local analytics too complex for edge devices, or temporary storage during connectivity interruptions.
Cloud: Centralized Intelligence
Cloud processing offers unlimited scale, advanced analytics, and multi-site aggregation. Choose cloud for historical analysis and ML model training, multi-site dashboards and reporting, and long-term data storage.
The Right Answer: Usually All Three
Most mature IIoT deployments use all three layers—edge for real-time control, fog for plant-level aggregation, and cloud for enterprise intelligence. Peunier's IIoT architecture practice helps clients design the right topology for their specific requirements.