Role of Fog Computing in Internet of Things Explained

BlogsCloudTechRole of Fog Computing in Internet of Things Explained

In today’s world of growing technologies, the industry experts have already created an alert regarding the cloud computing models that are currently being used for numerous IoT systems and suggested to move towards fog computing. 

They also warned that these cloud models are now ill-equipped to handle the current volume of data which is being generated by the billions of IoT devices on a daily basis.

Most of the early adopters of the IoT technology are now looking out for alternative computing models that are more secure and faster than cloud computing.

Brief on How Fog Computing is Important on the Internet of Things

Currently, cloud computing architecture is facing challenges in regard to the IoT applications it is being used for.

Also, it is noted that it lacks support for some trending IoT apps like AR, live video streaming, and gaming.

Since cloud computing is located centrally, it lacks location awareness. Whereas, fog computing is a part of cloud computing that is present in large servers under the cloud that can address these challenges and bridge the gap between IoT devices and cloud computing services.

In today’s world, to increase the efficiency of IoT applications, we need to process and analyze the data in real-time, which is generated by these IoT devices.

Fog computing can help us in doing so by bringing cloud computing, storage, and networking capabilities to the edge so that more secure, reliable, and efficient IoT applications can be made.

Fog computing has many different services and applications and also possesses the ability to connect various IoT applications in real-time.

With its low latency capabilities, fog computing is considered to be one of the best choices for applications like video streaming, gaming, etc.

Also Read: What are the Issues with Fog Computing?

Fog computing, when combined with the internet of things, will bring numerous benefits to various IoT applications as it can support the sensor networks, which will grow over the period of time.

Fog Computing Solutions to IoT

Low Latency

The actions, such as managing and analyzing data, etc., which are performed under the fog server, are located close to the end-user. Having low latency while working, helps the user and IoT devices to work faster, and generate real-time data efficiently.

Managing Network Bandwidth

The hierarchical data processing of fog computing devices bridges the gap between the cloud and the IoT devices.

This helps in data processing, which is needed to be carried out whenever an application demands.

Also, the repetitive request of data with its inflow and outflow requires bandwidth. With the presence of fog computing for IoT, the amount of data that is expected to be uploaded to the cloud lessens, eventually saving the network bandwidth.

Resource-Constrained Devices

Fog computing is of great help when it comes to handling operations of devices, which have limited processing capabilities. What fog computing exactly does is that lessens any associated complexities, costs, and power consumption.

Uninterrupted Computing Services

The presence of servers in fog computing is a boon for the organizations. Fog can run independently from the cloud as it has its servers, which are located near the users.

This step ensures that the user gets continuous, uninterrupted services, even in the case of no network connectivity to the cloud.

Securing IoT

Security functions are limited in the case of many resource-constrained devices. Fog computing helps in providing software and security updates to these devices. Also, it can be used to monitor the security status of the devices which are present nearby.


In recent years, the IoT has gained popularity and has become an integral part of our lives, mainly because of its ability to connect almost everything to everything.

But the presence of the traditional centralized cloud creates some issues like high latency and failure of the network.

Here, fog computing comes to the rescue by reducing latency, especially for time-sensitive applications.

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