What is edge computing in the 5G era?

You’ll probably be hearing a lot about edge computing over the next few years. We’ve become immersed in a society where millions of devices around the world are connected to each other. This flow of information needs to be as efficient and fast as possible, minimizing latency or delay between when a command is issued and when it’s 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, the Internet of Things encompasses everything. From the most mundane, like being able to watch a movie in the highest possible quality, to the most complex, like being able to operate on a patient without the presence of a doctor. This connection should be established as quickly and efficiently as possible. While the negative effects of latency are not dangerous in the former case, millimeter-level precision is required in remote surgery.

The advent of 5G has greatly reduced the latency of connecting devices to each other, but such networks alone are 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 and cloud computing

Before delving into the topic, it is important to understand what cloud computing is. Today millions of devices generate huge amounts of data, which is analyzed through the cloud. In other words, information is "transmitted" from our computers to external servers located in data centers that may be thousands of miles away, for example.

To illustrate this with a practical example, you connect to the internet from your phone and visit a specific website. To access the page, a request is sent to your phone operator, who then forwards it to the destination server. This server processes the data, responds, and sends it back to you so that you can access the site without any problems. Furthermore, the “cloud” is not only used to process data, but also to store it and run applications and services. The entire process is influenced by innovative technologies such as blockchain and artificial intelligence. According to a Microsoft press release, IDC predicts that there will be more than 41.6 billion connected IoT devices by 2025. The result is a massive amount of data and a lot of bandwidth consumption.

Edge computing: real-world applications

Edge computing aims to bring data processing as close as possible to the device that generates the data. This not only frees up bandwidth, but also minimizes response latency between the device and the server. In some scenarios, such as self-driving cars or health and industrial robots, this response should be as fast as possible.

Edge computing is proving to be an indispensable technology when it comes to connected cars. Cars will increasingly be equipped with cameras and sensors to monitor traffic and the driver’s visual environment in real time. Thanks to this environmental analysis, drivers will be able to receive real-time traffic information and predict various events.

In this regard, it is estimated that a single autonomous vehicle can generate more than 300 TB of data per year. It is inefficient to send all this information to a server far away from where it is generated. In this case, actions must be performed as close to the autonomous vehicle as possible. The delays in road safety are obvious: every incident must be reported in real time, immediately and without delay.

This is undoubtedly a huge advantage of edge computing. The technology means that data processing is closer to the user making the request (for example, they don't have to travel from Spain to a server in San Francisco), making the whole process more efficient and faster.

Edge computing is also very useful in machine learning models used for quality control of a company’s products. In the case of the cloud, information collected by sensors on the assembly line that determines whether a product meets quality standards must be transmitted to a server for analysis and then sent back. By bringing this process to the edge of production, sensors are much more efficient: they only need to send data about a product when they suspect it is not being produced well.

In summary, edge computing is a technology driven by the arrival of 5G that has multiple applications (quality control, road safety, video games and virtual reality in healthcare) and requires investments in network infrastructure and data analysis tools.