Edge computing: the missing link between cloud and IoT

What is edge computing?

Edge computing refers to a decentralized technological approach in which data processing takes place as close as possible to the data source. Such a setup differs significantly from traditional cloud computing, in which the processing and analysis processes take place centrally in a remote data center, because with edge computing, any processes are carried out as close as possible to the data source. This offers a much more reliable and efficient solution, especially when dealing with real-time data (e.g. from sensors).

Challenges of the public cloud for the Internet of Things (IoT)

A study by Gartner predicts that the amount of data generated outside of data centers will increase to around 75% by 2025. The figures confirm the clear need for a concept dealing with externally generated knowledge. However, traditional hosting in the public cloud is clearly reaching its limits when dealing with the Internet of Things, as the significant distance between the data provider and the processing facility means that low latency can no longer be guaranteed. Nevertheless, this plays a particularly important role in real-time applications. Here are a few real-life examples:

The first application can be found in the intelligent monitoring of a patient's vital parameters. Today, there are already devices that monitor and analyze heart rate, blood pressure and oxygen saturation in real time to detect abnormal developments at an early stage and warn of medical emergencies. However, carrying out these analyses in the public cloud would make the devices unreliable and largely negate the technological advantages. The negative consequences of limited availability could be devastating. To secure the digital future of healthcare, it is therefore essential to find local solutions that can still be integrated into the digital world.

Specific examples can also be found in the world of cars. In the field of autonomous driving in particular, various sensors and cameras generate a stream of data that needs to be processed quickly and reliably in order to provide the desired safety and comfort functions permanently. Thus, high latencies would result in a deterioration of the service and may even endanger individuals. In addition, the issue of data protection is always a point of discussion, especially when it comes to camera recordings. However, these risks can be minimized as far as possible by transferring data processing to the vehicle.

Advantages of edge computing

As you have already read, edge computing offers a number of advantages for special use cases that make it an attractive addition to the classic public cloud. A look at the figures confirms this. According to a summary study by Markets and Markets, 60% of large companies are already using this technology. There are many reasons for this:

• Lower latency
  Applications that are operated in edge computing setups have lower latency and are more reliable. They can therefore also be used for time-critical applications.
  
  
• Data protection and compliance
  Sensitive data can easily be stored and processed locally, facilitating the ability to adhere to complex data protection guidelines and compliance regulations.
  
  
• Robustness and reliability
  Decentralized data processing ensures greater availability of individual services, as single points of failure can be avoided.
  

Conclusion

In an ever-changing digital world, edge computing is an important addition to the traditional public cloud and helps to overcome the increasing challenges of networking. While the public cloud will continue to play a central role in the future, edge computing will also become increasingly important for the operation of critical infrastructure components in order to close the gap between the public cloud and IoT.