Edge computing is an emerging technology that enables efficient data processing because large amounts of data can be processed close to the data source, thereby reducing Internet bandwidth usage. This both reduces costs and ensures that applications can be used efficiently at remote locations. Additionally, the ability to process data without putting it into the public cloud adds a useful layer of security to sensitive data.
Here are three reasons why edge computing is critical to IoT:
1. Efficiency, reducing centralized cloud computing to reduce costs by reducing the frequency and scale of data transmission.
2. Security because the data is closer to where it was created.
3. Scalability, because edge computing is basically distributed computing, which means it can improve elasticity, reduce network load, and be easier to expand.
Currently, most data management and analysis occurs in the cloud or data center. In the edge computing model, however, sensors and connected devices transmit data to a nearby edge computing device that is housed in a local data center, rather than transmitting it back to the cloud or a remote data center.
With edge computing, data is processed by the device itself or a local computer or server, rather than being transmitted to a remote data center. Edge computing enables data flow acceleration, including real-time data processing and no latency. It allows smart applications and devices to respond to data almost immediately as it is created, eliminating lag time.
In the Internet of Things era, with digital transformation, it requires more agile connections, more efficient data processing, and better data protection. Edge computing can effectively reduce bandwidth requirements, provide timely response, and protect data privacy. It can be seen that edge computing is playing an increasingly important role, and edge computing is becoming the development pillar of the Internet of Things.