Which statement best differentiates fog computing from traditional cloud computing?

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Fog computing brings data processing closer to where data is produced, at the edge of the network—on gateways, routers, or small data centers near sensors. This proximity lets the system analyze data and respond in real time, reducing the time between sensing an event and acting on it. The main advantage is lower latency, which is crucial for IoT applications like real-time monitoring or automated control.

Traditional cloud computing, by contrast, sends data to centralized data centers that may be far away, adding communication delays and potentially using more bandwidth because raw or large volumes of data travel over the network before any processing happens. Fog doesn’t replace the cloud; it sits between the edge and the cloud, handling processing locally and then forwarding results or only essential data to the cloud for deeper analysis, storage, or learning.

So, the best statement highlights that fog computing processes data at the edge to cut latency. It also helps to remember that fog can reduce bandwidth needs through local filtering and pre-processing, it doesn’t eliminate cloud services, and it does handle data from sensors.