Edge computing architecture can be visualized as a pyramid consisting of multiple layers with edge devices at the bottom.
The edge and IoT devices can collect data, run analytics, apply artificial intelligence rules to collected data, and even store some data locally. These edge devices can handle real-time decision-making and analysis without the involvement of the edge server or the enterprise server.
Responsible for monitoring and maintaining millions of devices and deploying or upgrading apps on these devices, the edge server remains connected with the devices.
It does so with the help of agents installed on each of these IoT devices. If a device doesn’t have enough analysis capabilities, then the device sends data to the edge server for further analysis.
This bridge between the edge and the cloud usually has more processing power than the edge servers. This layer has IoT gateways or fog nodes that generally execute additional filtering and analysis.
There is no strict rule to have this layer; it is optional, and many edge systems can be set up without the Fog layer.
This layer is responsible for accumulating data received from all edge devices and fog nodes and storing it in data warehouses. This layer has ultimate processing capabilities and runs Big Data analytics.