Edge computing is a computing architecture model that shifts data processing and analysis from central servers or the cloud closer to the “edge” of the network — that is, nearer to the devices and sensors that generate the data.
Main purpose:
To reduce latency and bandwidth usage, improving responsiveness and efficiency in applications that require real-time performance, such as autonomous vehicles, the Internet of Things (IoT), or augmented reality.
Key features:
- Proximity: Computation happens near the data source (devices, sensors, local routers).
- Efficiency: Less need to send massive amounts of data to distant data centres.
- Reliability: Services can continue even with intermittent cloud connections.
- Security: Sensitive data can be processed locally, lowering transmission risks.
Example:
A video surveillance system with facial recognition that processes images in situ on a local device, without sending every video stream to a central server, enabling immediate detection.
