What is fog computing? And how it works?

What does fog computing mean?

A fog computing infrastructure consists of applications, data, and computers that are located somewhere between a data source and a cloud.

As with edge computing, fog computing brings the power and advantages of the cloud closer to the point of creation and action.

Both fog computing and edge computing bring intelligence and processing closer to where the data is created, so the terms are often used interchangeably.

The purpose of this is often to improve efficiency, but it may also be to ensure compliance and security.

Just as fog concentrates on the edge of a network, the fog metaphor comes from the meteorological term for a cloud close to the ground.

This term is often associated with Cisco; its product line manager, Ginny Nichols, is believed to have coined it. A registered name, Cisco Fog Computing, refers to a technology that is open to the public.

In what way does fog computing work?

Fogging is a short-term analytics technique at the edge complementing cloud computing for long-term analysis.

Data is generated and collected at edge devices and sensors, but they lack the computing power and storage to perform advanced analytics and machine learning.

Cloud servers can do this, but they are usually too far away to process the data and respond in a timely manner.

Furthermore, connecting all endpoints to the cloud and sending raw data to it over the internet can have privacy, security, and legal implications, especially when dealing with sensitive data regulated differently in different countries.

Smart grids, smart cities, smart buildings, vehicle networks, and software-defined networks are some of the most popular applications of fog computing.

How does fog computing benefit businesses?

As with any technology, fog computing has its pros and cons. There are several advantages to fog computing, including:

• Conserving bandwidth- By reducing the amount of data sent to the cloud, fog computing reduces bandwidth consumption and associated costs.
• A faster response time- Due to the fact that the initial data processing occurs near the data, latency is reduced, and overall responsiveness is improved. By providing millisecond-level responsiveness, data can be processed in near-real time.
• It is network-agnostic- While fog computing typically uses LANs instead of devices, as with edge computing, the network could be considered part of the fog computing architecture. However, fog computing is network-agnostic, since the network can be wired, wireless or even 5G.

What are some of the applications of fog computing?

• Monitoring and analyzing the patient's condition is possible with it. Doctors can be alerted in case of an emergency.
• In order to monitor high-speed trains in real-time, we want as little latency as possible.
• Gas and oil pipeline optimization can be achieved using it. Data generated by this system generates a tremendous amount of data, which is inefficient to store in the cloud and then analyze.

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