Fog Computing & Distributed Processing in Edge Devices

Fog Computing allows for fast and efficient data processing and analysis in Edge Devices while conserving bandwidth. Read on to learn more.

Fog computing is growing at an exponential rate in the current times. Fog computing is soaring high in the tech and specifically, IoT arena for filling in the increasing demand for low latency and high throughput applications, thanks to such high growth statistics. As the number of Internet of Things (IoT) applications grows, so does the scale of the fog computing market.

Lets Understand what exactly is Fog Computing?

In simple terms, fog computing is a decentralised computing infrastructure that is flexible enough to split bandwidth traffic to analyse data at the edge. It is positioned between the devices that produce the data and the cloud. Fog is a type of cloud that is closer to the ground than cloud.

EVERY MINUTE, THE INTERNET OF THINGS GENERATES A HIGH VOLUME OF DATA, AND THE DATA GENERATED VARIES IN NATURE AS WELL. THIS DATA MUST BE PROCESSED QUICKLY IN ORDER TO BE USED WHEN THERE IS A NEED FOR IT.

Benefits of fog computing

Conserving Network Bandwidth – As is well known, data processing takes time and resources, therefore data must frequently be transported from edge devices to the cloud and back. This isn’t truly necessary because cloud-intensive processing isn’t required for all analyses.

Reduction in Latency – Because the data no longer needs to be transmitted to the cloud for processing, computation may now be done closer to the data’s source, resulting in a reduction in latency.

Fog computing vs edge computing

Fog computing and edge computing are often used interchangeably since both technologies attempt to analyse data fast and intelligently closer to the data source. However, the main distinction between fog computing and edge computing is the location of compute resources and the process standard.