What is Edge Computing in the 5G Era?

Over the next few years, you’ll probably hear a lot about Edge Computing. We are already immersed in a society where millions of devices around the world are interconnected. This flow of information must be as efficient and fast as possible, minimizing the latency or delay between when a command is given and executed. So what is Edge Computing technology and how does it relate to 5G connectivity? Let’s take a closer look.

Let’s get straight to the point: what is edge computing?

Today IoT is all encompassing. From the most banal, like being able to watch a film on demand with the highest possible quality, to the most sophisticated, like being able to operate on a patient without the presence of a doctor. This connectivity should be accomplished as quickly and efficiently as possible. While in the first case the negative effects of latency are not dangerous, millimeter precision is required in remote surgery.

The advent of 5G has significantly reduced the latency of devices connecting to each other, but this network alone is not enough to meet today’s needs. This is where Edge Computing technology comes in: bringing data processing closer to where the data is generated.

Edge Computing vs Cloud Computing

Before delving into the subject, it is important to understand what Cloud Computing is. Today’s millions of devices generate a huge amount of data that is analyzed through the cloud. In other words, information travels, for example, from our computer to an external server, located in a data center which can be thousands of kilometers away.

To illustrate this with a practical example, you connect to the internet from your mobile phone and go to a specific website. To access the page, a request is sent to your telephone operator, which forwards it to the destination server. This server processes the data, replies and returns it to you so that you can access the site without problems. Furthermore, the cloud is used not only to process data, but also to store it and run applications and services. The whole process is influenced by innovative technologies, such as Blockchain and Artificial Intelligence. According to a press release from Microsoft, IDC predicts that there will be more than 41.6 billion connected IoT devices by 2025. The result is a huge amount of data and a lot of bandwidth consumption.

Edge Computing: Practical Applications

Edge Computing aims to bring data processing as close as possible to the devices that generate it. This not only frees up bandwidth, but also minimizes the response latency between the device and the server. In some scenarios, such as automated cars or healthcare and industrial robotics, this response should be as rapid as possible.

In the case of connected cars, Edge Computing is proving to be an indispensable technology. Cars will increasingly be equipped with cameras and sensors that monitor traffic and the driver’s visual environment in real time. Thanks to this environmental analysis, the driver will be able to receive traffic information in real time and anticipate various accidents.

In this regard, it is estimated that an autonomous car can generate more than 300TB of data per year. It is not efficient to send all this information to a server far away from where it is generated. This should be done as close as possible, in this case, to the autonomous vehicle. The latency of road safety is evident: every accident must be reported in real time, immediately and without delay.

This is undoubtedly the great advantage of Edge Computing. This technology means that data is processed closer to the user making the request (it doesn’t have to travel from Spain to a server in San Francisco, for example), making the whole process more efficient and faster.

Edge computing can also be very useful in machine learning models for quality control of a company’s products. In the case of the cloud, information collected by sensors on the assembly line that determine whether a product meets quality standards must travel to the server to be analyzed and then sent back. By taking this process to the edge of production, sensors are more efficient: they only need to send data about a product if it is suspected that it has not been produced well.

In conclusion, Edge Computing is a technology driven by the arrival of 5G, a technology with multiple applications (quality control, road safety, video games and virtual reality in the healthcare sector) which requires investments in network infrastructure and data analysis tools .

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