Do you fantasize about using remote server hosted on the internet?

One or two decades ago, you could call it a beautiful dream. Today, it’s a reality. You can store, manage & process data via cloud computing on the remote server. It means that you don’t need to own a private server.

Like technology devices, the disruption is seen in the computing as well. Edge computing is an addition to this fact. The Internet of Things (IoT) are bombarding in almost every domain. Calling these devices as the factory of data manufacturing will not be a hyperbole. These devices produce multitudes of data every sec. Now, the biggest challenge is to deal with the processing of those zillions of datasets.

There are millions of data chunks that play no game-changing role after the data processing. Can you imagine how much time, space and money an enterprise devote to process its data produced from sensors, controllers, and other connected devices? What about the cost of maintenance of IT infrastructure, cloud computing and IT managed services? You can’t get them off.  

It will figure out in millions to billions. It costs an arm and a leg that would be a big loss. To combat these problems, the edge computing was evolved.

What is Edge Computing? 

The cloud computing takes your data to the far located data warehouses to store and process. The edge computing creates a shortcut. It means that your data won’t be transmitted to the data center. Rather, the data sets would be transmitted to the nearby computing device. It can be a laptop or server. That device becomes an edge of the network where filtering, processing and optimization take place. 

Thereby, you don’t need to wait for the data transmission. Neither can you wait a second to analyze those sets of data and put them into action.

In all, the edge computing is a network mesh up that store and process critical data locally. Mostly, such edges are set within the ambit of 100 square feet. 

What are the edge terminologies?

Before moving further, you need to be well versed with the terms related to this kind of computing. Bear in mind that the IT solutions providing companies do use them as its taxonomies.

1. Edge devices: These are the data producing devices. They can be sensors. They can be computers. They can be CCTV cameras. They can be any machine that delivers data.

2. Edge: It can be anything that performs the core service. For example, the cutting machine would be an edge of the timber factory. The phones would play the same role for a customer care center.  Likewise, there are several arenas where the edge would be a local asset that performs the key role.

3. Edge Gateway: It’s a connecter to link the edge device with the edge. It sits between the external internet and the local intranet that the inbound devices use. You can imagine it like a router.

4. Fat Client: The IT experts use this term to denote the software that wisely processes some data on the edge devices.  There exists the thin client as well that don’t let data transmission to occur.

5. Edge Computing Equipment: These are a range of tools/accessories that can fit in the edge computing landscape via the internet connection. Let’s say, a landline connection needs wires, sensor devices and other machines to create a broadband conduit. Likewise, the edge computing equipment serves the similar purpose.

6. Mobile Edge Computing: It implies the embedding of edge computing in the telecommunication system.

How can we consider the Edge Computing as the future of IT infrastructure? 

As foretold, it is transparent that the cloud computing eats up a big fragment of your time in data traversing over the network. But the edge computing frees you from such delaying factors. The data transmission through the Internet of thing’s devices doesn’t work intermittently. Several IT infrastructures point finger at their efficiency. The problem shoots during the connectivity to a central cloud.

The edge computing helps you to sail through such hoops that may generate latency. One more point worth considering is the traffic. Since the data navigate from local devices to the cloud, therefore, the network traffic doesn’t congest.

Thereby, the owner generally doesn’t give a second thought regarding its usage.

Let’s consider an example.

A renowned company ‘Envision’ looks into the data produced by the sensors of 20,000 wind turbines. It’s a huge network with 3 million sensors as data producers. At a time, they produce upto 20 terabytes. By deploying this efficient computing, the Envision avoid messing around for deep analysis. The minutes long analysis cuts to a few seconds. Consequently, it has scrolled up the productivity of the turbines by 15 percent, according to business sprint.