Edge computing is the local and decentralized data processing at the network edge. It thus defines itself as part of a distributed computing architecture, where data processing occurs in the periphery. In other words, where users utilize the information.
Background
Edge computing is revolutionizing data processing and transmission on millions of devices worldwide. Originally, the technology was introduced to reduce data transmission distances. However, it now encompasses much more: The rapid growth of the Internet of Things (IoT) and the emergence of new applications requiring real-time data emphasize the importance of this type of computing.
Edge Computing and IoT
Edge computing and the Internet of Things (IoT) are closely interconnected and together offer innovative solutions for many application areas. For instance, a typical application for edge computing can be found in industrial manufacturing. IoT sensors monitor machines in real-time and collect data on temperature, vibration, and other relevant parameters. The processing of this data occurs directly at the ‘edge’ or at the network’s periphery, in immediate proximity to the machines. Thus, they are not first sent to central servers as is usually the case.
An example of this is a production facility where any delay could cause critical failures. By using edge computing, the captured data is analyzed immediately. In case of deviations, the system reacts instantly, for example, by shutting down a machine before greater damage occurs.
Autonomous vehicles also benefit from this new type of data processing. These vehicles are equipped with numerous sensors that continuously collect environmental data. Edge computing enables the processing of this data in real-time directly in the vehicle, allowing for lightning-fast decisions to be made, for example, to avoid obstacles or adapt to traffic conditions.
Local data processing not only significantly reduces reaction times but also relieves bandwidth, as less data needs to be sent to central servers. Additionally, data security also benefits, as sensitive information is processed locally and not transmitted across the entire network.
Overall, edge computing improves the efficiency and reliability of IoT applications by enabling fast, local data processing and reducing dependence on central data centers.
Advantages
What does decentralized data processing mean? Instead of sending data to a remote data center, with edge computing, it is processed directly on the devices or in their immediate vicinity. This is done primarily to reduce latency times: A major advantage especially for applications that need to process data almost in real-time. Additionally, companies can save costs through local data processing, in the form of bandwidth, data volume, and cloud storage costs. Sensitive data and specialized algorithms remain on-site and are not transferred to the cloud.
- Faster data processing
- Lower latency times
- Security of sensitive data
