Fog computing (also known as fog network or fogging) is a decentralized computing infrastructure in which some of the data, computation and storage between the cloud and the device is handled in a distributed manner, thereby acting as a mediator node between the device and the cloud (remote server).
Although the device can gather and process the data, sometimes it gets difficult for the device to compute (mainly due to complexity issues). Moreover, sending data traffic frequently to the remote cloud stresses the network bandwidth. To solve this issue, fog computation is introduced to complement cloud servers and allow short-term data computation and transfer at a local level which results in traffic control and provide a real-time response to the device.
The following are the benefits of implementing fog computing:
Since data is dealt with locally (closer to the device) and not on the cloud, it provides low latency and less access time as there is less data flow back and forth to the cloud.
Provides better data privacy as less data is passed over to the cloud, which is more prone to attacks.
It reduces stress on the network bandwidth and the operation cost.
Some of the drawbacks of fog computing are as follows:
Since fog computing is implemented at the LAN level, it reduces the user's flexibility by confining them to one place.
Security is compromised by adding an additional layer between the cloud, and the device can cause spoofing and a man-in-the-middle attack.
It increases the hardware costs by adding another layer of LAN infrastructure.
Fog computing is used to support many technologies, including:
Monitoring self-driven cars and alerting drivers if an issue arises by giving real-time responses.
Used in smart grids to enable a two-way flow of electricity and to detect any changes in usage.
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