Fog computing is a distributed computing model that places storage and processing closer to where data is created, instead of sending everything to a distant cloud data center. It is especially useful for IoT systems and time- sensitive applications because it reduces latency and bandwidth use.

How it works

In a fog setup, data from devices like sensors, cameras, or machines is first handled by nearby computing nodes, often called fog nodes. Those nodes can filter, analyze, or act on the data locally, then send only the useful results to the cloud for deeper analysis or long-term storage.

Why it matters

Fog computing helps when:

  • Fast response is important, such as in industrial automation or traffic systems.
  • Sending all raw data to the cloud would be too slow or expensive.
  • Local processing can improve reliability and reduce network load.

Fog vs cloud

Cloud computing centralizes processing in remote data centers, while fog computing spreads processing across devices and nearby network nodes. In practice, fog often works with the cloud rather than replacing it: fog handles immediate decisions, and the cloud handles heavier analytics or storage.

Simple example

A factory sensor detecting overheating can trigger a local fog node to shut down a machine instantly, while also sending a summary to the cloud for later reporting. That avoids waiting for a round trip to a faraway server.

TL;DR: Fog computing brings cloud-like processing closer to the edge of the network so systems can respond faster, use less bandwidth, and support real-time IoT applications.