With IoT projects, often it's better to use fog computing where compute, storage and communications resources are place in a continuum between the cloud and the edge.

What are the use cases of fog computing? The applications of fog computing are many, and it is powering crucial parts of IoT ecosystems, especially in industrial environments.

The differences between general cloud computing and its “edge” and “fog” computing offshoots have stymied even many professionals since their introduction. But when it comes to general consumers, IT ...

A fog computing architecture performs analytics or run applications on anything from the network center to the edge -- wherever it makes the most sense, economically and technically .

Fog computing enables real-time data processing, which is critical for applications that require real-time decision-making, such as autonomous vehicles and smart cities.

Choosing between edge and fog computing depends on the application’s need for speed, scalability, and the level of coordination across devices.

While cloud computing carries data back to a central server for storage and analysis, fog computing enables analytics and other functions to be performed at a network’s edge, right at the data source.

Fog brings the power of the cloud closer to the network edge and improves latency for mission-critical applications.