Fog computing …. A brief explanation

Muhammad Adel February 3, 20214,027

Reading Time: 3 minutes

It is insane how much data we produce every single moment. As we now have a solid definition of IoT (Internet of Things), we expect and experience unprecedented volume and variety of data.

We used to go for available solution which can manage and compute this amount of data…. The cloud.

But, how fast the edge devices use IoT need to access its data! Imagine it.

So, we need this data’s logical location to be more adjacent and closer to the deice than the cloud. We started to think about Fog computing

What is Fog Computing?

Fog computing, also called fog networking or fogging, describes a decentralized computing structure located between the cloud and devices that produce data. This flexible structure enables users to place resources, including applications and the data they produce, in logical locations to enhance performance.

Fog computing security issues also provide benefits for users. The fog computing paradigm can segment bandwidth traffic, enabling users to boost security with additional firewalls in the network.

The history of Fog Computing

In 2012, Cisco introduced the term fog computing for dispersed cloud infrastructures. The aim was to promote IoT scalability, i.e., to handle a huge number of IoT devices and big data volumes for real-time low-latency applications.

History of communication and distributed systems

But what is the difference between Fog Computing and Edge Computing?

The goal of edge computing is to bring the data sources and devices closer together, eliminating the time and distance to process. In theory, this in turn improves performance and speed of applications and devices.

Fog computing, also involves bringing computing to the network’s edge. However, it also refers to the standard for how this process should, ideally, work.

By moving storage and computing systems as near as possible to the applications, components, and devices that need them, processing latency is removed or greatly reduced. This is especially important for Internet of Things-connected devices, which generate massive amounts of data. Those devices experience far less latency in fog computing, since they are closer to the data source.

Cloud, fog, edge, and things. Source: rtinsights.com

Fog Computing Advantages

Minimize latency. Keeping analysis closer to the data source, especially in verticals where every second counts, prevents cascading system failures, manufacturing line shutdowns, and other major problems. The ability to conduct data analysis in real-time means faster alerts and less danger for users and time lost.

Conserve network bandwidth. Many data analytics tasks, even critical analyses, do not demand the scale that cloud-based storage and processing offers. Meanwhile, connected devices constantly generate more data for analysis. Fog computing eliminates the need to transport most of this voluminous data, saving bandwidth for other mission critical tasks.

Reduce operating costs. Processing as much data locally as possible and conserving network bandwidth means lower operating costs.

Enhance security. Whether in transmission or being stored, it is essential to protect IoT data. Users can monitor and protect fog nodes using the same controls, policies, and procedures deployed across the entire IT environment and attack continuum to provide enhanced cybersecurity.

Improve reliability. Because IoT devices are often deployed under difficult environmental conditions and in times of emergencies, conditions can be harsh. Fog computing can improve reliability under these conditions, reducing the data transmission burden.

Deepen insights, without sacrificing privacy. Instead of risking a data breach sending sensitive data to the cloud for analysis, your team can analyze it locally to the devices that collect, analyze, and store that data. This is why the nature of data security and privacy in fog computing offers smarter options for more sensitive data.

Boost business agility. Only by knowing what resources customers need, where they need those resources, and when the support is needed can businesses respond to consumer demand quickly. Fog computing allows developers to develop fog applications rapidly and deploy them as needed. Fog computing technology also allows users to offer more specific services and solutions to their customers and locate data and data tools where they are best processed—all based on existing computing capabilities and infrastructure.

Fog computing challenges include a heavy reliance on data transport. The rollout of the 5G has improved this issue, but limited availability, lower speeds, and peak congestion are all issues. Both speed and security at fog nodes are other potential issues that demand attention.

Here is a great video about the fog computing and its impact on 5G. Click here.