Possible you read how the oil and gas industry uses IoT to host hundreds and thousands of sensors at its facilities. With so much input data that all these multiple IoT devices transmit, it is no longer feasible to transfer data to the cloud or a shared data Center for processing: some mechanisms for analyzing and responding to data from the IoT can be implemented locally, in a place where this telemetry is removed, and the data itself is produced. That is, the term "Edge Computing “or” Boundary computing "does not mean some physical boundary, not some abstract type of “cutting edge technology”, but that all actions take place “somewhere out there on the ground”, and not in the local data center and not in the cloud.
Typical examples of boundary calculations include:
- Analysis of video from surveillance cameras or other sources
- Self-driving cars
- Robot control
That is, what is long/expensive/pointless to transfer somewhere, loading communication channels at a time when the application is running “in real time”. In addition, in a sense, on-premises data processing saves money by reducing the amount of data transferred and stored in a cloud location. The concept of Edge computing has emerged thanks to the exponential growth of IoT devices that connect to the Internet either to get information from the cloud or to deliver data back to the cloud. And many IoT devices generate huge amounts of data in the course of their operation that are inherently unnecessary after they are processed.
Think of devices that monitor production equipment in a factory, or an Internet-connected video camera that sends real-time video from a remote office. While a single device producing data can transfer it over the network quite easily, with the growth of such devices, there are already problems with delays. Instead of a single video camera transmitting live footage, multiply it by hundreds or thousands of devices. Not only will quality suffer because of the delay, but the bandwidth costs can be huge.
Peripheral computing equipment and services help solve this problem by providing a local source of processing and storage for many of these systems. An edge gateway, for example, can process data from an edge device and then send only the data you need back through the cloud, reducing the need for bandwidth. Or it can send data back to the edge device in case the application needs to run in real time.