Top Fog Computing Applications: A Simple Guide For 2021

Introduction

Cloud computing stores and processes data in data centers that are situated in remote locations. The data generated from many devices is vast with the launch of IoT. Fog computing and fog computing applications came into being as a result. Fog computing is a distributed architecture, and the smart devices present at the edge of the network can control some of the application processes. Although most programs in the cloud are also handled.

In basic words, the whole process that has to be performed in the cloud is replaced by smart devices at the edge of the network. The volume of data being transmitted to the cloud will be limited. In this article, we will learn, fog computing applications, fog architecture, fog layer, fog computing applications list and, the benefits of fog computing.

In this article let us look at:

1. What is Fog Computing?
2. Origin of Fog Computing
3. Benefits of Fog Computing
4. Fog Computing Applications

1. What is Fog Computing?

Fog computing is a decentralized computer architecture that processes and preserves information between the source of origin and the resources of the cloud. This contributes to the minimization of overhead data transfer and ultimately increases computational efficiency on cloud networks by reducing the need to process and retain vast quantities of superfluous data. The Fog computing paradigm is primarily driven by a continuous rise in Internet of Things (IoT) devices, where an ever-growing amount of data is generated from an ever-expanding array of devices (in terms of scale, variety, and velocity).

2. Origin of Fog Computing

Cisco, which recorded the name ‘Cisco Fog Computing,’ which played on cloud computing when the clouds are high in the atmosphere, and the fog applies to the clouds near the ground down, is synonymous with the term fog computing. An OpenFog Collaboration was set up in 2015 with founding members ARM, Cisco, Dell, Intel, Microsoft, and Princeton University, and additional participating members including GE, Hitachi, and Foxconn. The loosely allied, and largely synonymous, concept ‘edge computing’ was introduced by IBM (although not exactly in some situations).

3. Benefits of Fog Computing

• Greater Market Agility: Developers can seamlessly create fog computing applications and launch them whenever appropriate by using the right set of instruments. Fog apps push the system to run in a way that customers require.

• Better security: It is possible to secure fog nodes using the same controls, processes, and policies as you use in other IT environment areas.

• Deeper Insights with Privacy Control: Instead of uploading it to the cloud for processing, confidential data can be processed locally. The IT team will manage the instruments that capture, process, and store data and manage them.

• Reduced Operating Cost: By processing chosen data locally, Fog computing can conserve network resources instead of uploading it for review to the cloud.

• Fog Computing applications: In a cloud-based management system, Fog Computing functions better to provide control and deeper analysis across a variety of nodes. Wind electricity, transportation, smart cities, security, and smart buildings are among others. Let’s look at some of the real-life cases of where fog computing can be useful and how.

• Fog Computing in Smart Cities: There is a range of problems facing big cities, including public safety, sanitation, heavy electricity consumption, and community services. Through deploying a network of fog nodes, the solution to these problems exists in a single IoT network.

4. Fog Computing Applications

• Linked vehicles: Self-driven or self-driven vehicles are now available on the market, producing a significant volume of data. The information has to be easily interpreted and processed based on the information presented such as traffic, driving conditions, environment, etc. All this information is processed quickly with the aid of fog computing.
• Smart Grids and Smart Cities: Energy networks use real-time data for the efficient management of systems. It is necessary to process the remote data near to the location where it is produced. It is also likely that data from multiple sensors will be produced. Fog computing is constructed in such a manner that all problems can be sorted.
• Real-time analytics: Data can be transferred using fog computing deployments from the location where it is produced to different locations. Fog computing is used for real-time analytics that passes data to financial institutions that use real-time data from production networks.

Conclusion

Fog computing provides cloud computing to manage the greater array of regular IoT data generated. It helps to overcome the problems of data velocity, variety, and volume explosion. It also increases understanding and reaction to incidents by eradicating an intellectual round trip to the cloud.

Also, discharging gigabytes of the network from the prime network helps minimize the costs of extra bandwidths. Furthermore, by analyzing it inside the organization, it can protect the fragile Internet of Things content. Therefore, businesses that implement fog computing achieve quicker and deeper insights, leading to improved market agility, enhanced protection, and a higher quality of operation.

If you are looking for an extensive course in Cloud Computing, then the 5.5-month online Postgraduate Certificate Program In Cloud Computing offered by Jigsaw Academy can be of help. This program helps interested learners become complete Cloud professionals. 

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