Edge Computing: We are increasingly diving into the data universe, driven mainly by technologies such as Augmented Reality, the Internet of Things (IoT) and Virtual Reality.

However, these novelties still come up against an obstacle that prevents them from becoming even more popular: connectivity problems. In this context, Edge Computing emerges as the solution that promises to facilitate the implementation of these resources.

The growth of the technologies mentioned above has increased the demand for data processing and the need for security and agility. Given this, Edge Computing comes to optimize the use of devices connected to the internet through micro data centers that process, store and classify data locally, keeping them close to the user. In this post, we will better explain what it is and the goals of Edge Computing. Check out!

What Is Edge Computing?

To better understand this solution, it is necessary to talk about the Internet of Things, in which data is collected by the device connected to the user’s network. A smartphone, for example, compiles the stored data and sends it to be processed in the cloud or a processing center.

When it comes to Edge Computing, instead of taking the data to the cloud, it classifies this information locally. It separates it so that it can be processed within the device itself. This reduces data traffic, adding agility and security to the process.

It can be said that data is processed at the ends of the network, and only a slice of it is sent — a factor that contributes to leveraging technologies that depend on agile data processing and latency to be effective. According to Gartner, Edge Computing is one of the main trends in strategic technologies for the coming years, as it adds competitiveness to the business.

How Does It Work In Practice?

Many tech professionals see Edge Computing as an “anti-latency” model, as it is best applied to IoT tools that lose efficiency when connecting to a central Cloud Computing.

Using edge computing, the company no longer sends its data directly to cloud computing. That’s because they are compiled, and those most frequently requested by the user are stored on the device. The least requested information stored for a longer time is transferred to the cloud.

This process is possible thanks to a structure composed of intermediary devices, known as gateways, which sort the data, separating them between those that must be processed at the Edge and those sent to the cloud from an intelligent system.

In this way, only data defined as relevant circulates through the network, reducing information traffic on this channel, which is advantageous for places that use a poor connection, as this makes access to data difficult.

What Are The Differences Between Edge Computing And Cloud Computing?

The main difference between the two concepts is how the data is processed. Cloud Computing consists of a solution that provides data processing and storage services based on data centers that are accessed online, that is, in the cloud. Thus, the company can reduce the use of physical structures and servers, gaining flexibility in its operations and reducing costs.

On the other hand, Edge Computing changes the Cloud Computing perspective, as data is processed locally, that is, on the device on which it is produced. This feature reduces data transmission time (latency).

What Are Edge Computing’s Goals?

Because it improves the connectivity and communication of companies, Edge Computing is a strategic technology and, therefore, can leverage the performance and results of companies. See below the main objectives of this solution and how they benefit your business.

Improve The Functionality Of Services

Adopting Edge Computing can significantly improve the end-user experience by making it more predictable and improving its quality. In addition, it is a scalable network that reduces performance issues and downtime, as well as the cost associated with your infrastructure and the complexity of managing your processes.

Reduce The Impacts Of Service Failures

The entire structure integrated into this computing model ensures that the intelligent tools work without disruption, even if offline or the internet has an intermittent connection.

Considering this, this architecture is ideal for organizations that need to analyze data in remote areas and identify possible failures of equipment that is not connected to the cloud.

Decrease Latency

Having low latency is essential for the smooth running of several applications simultaneously. Edge computing contributes to the achievement of this objective, considering that the tools start to be executed locally. In this scenario, the data travels along a shorter path. Therefore, the response time of applications is also reduced.

Increase The Protection Of Sensitive Data

At Edge Computing, data is stored in different locations, enhancing company information’s privacy and security. After all, it has mechanisms that filter sensitive data and process it on the devices themselves, transmitting only non-critical data to the cloud. This factor facilitates the organization’s compliance with the General Personal Data Protection Law (LGPD).

Bringing Responsiveness To IoT Devices

The low latency of edge computing brings much more responsiveness to IoT devices. This means that companies also optimize data analysis to perform them in real-time. Another critical point is that it collects, stores, and analyzes data close to the user, data traffic coming and going, allowing companies to choose which services will be processed on the device and which should be transmitted to the cloud to reduce IoT costs.

Also Read: Growth Hacking: What Is It, And Why Apply It To Your Company?

Previous articleData-Driven API: 7 Tips To Follow This Path
Next articleAI Implementation Landscape In The Automotive Industry?
We publish beyond technologies...

LEAVE A REPLY

Please enter your comment!
Please enter your name here