Edge Computing vs. Fog Computing: Key Differences

This article compares edge computing and fog computing, highlighting their key differences. A tabular comparison is also provided.

What is Edge Computing?

Edge computing is an optimization of cloud computing that aims to move computation closer to the data source, i.e., where the data is being generated. It refers to delivering computing capabilities at the network’s edge to improve performance, reduce operating costs, and enhance the reliability of applications and services.

Edge computing utilizes nodes known as “Edge Nodes,” where data processing occurs.

Image Courtesy: IEEE

Edge computing finds applications in various fields, including surveillance, IoT (Internet of Things), autonomous vehicles, Industry 4.0, healthcare, and financial services, among others.

What is Fog Computing?

Fog computing extends the cloud closer to the devices that produce or generate data. These devices are referred to as fog nodes. A fog node is any device with network connectivity, storage, and computing capabilities. Examples include switches, controllers, routers, servers, and cameras. Fog computing is sometimes used interchangeably with edge computing.

Fog computing is primarily used for the following:

• Analyzing time-sensitive data at the network edge, close to its origin, rather than sending large amounts of data to the cloud. It acts on IoT data in milliseconds.
• Sending selected data to the cloud for analysis and long-term storage.
• Providing services to a large number of devices spread across a vast geographical region.
• Addressing devices subjected to extreme conditions.

Difference between Edge Computing and Fog Computing

The following table outlines the key differences between edge computing and fog computing.