What is Edge Computing?
Edge computing is the computing that comes from placing the workload at the edge of the corporate network that is creating the data. The “edge” is defined as the place where the final devices can access the rest of the network devices, such as laptops, phones, desktops, machines, routers and sensors.
This technology is used to connect IoT devices so that they can efficiently deliver data, receive instructions quickly, and download software updates from the cloud or data center without any hassle. Edge Computing is a new approach to network architecture where the first cloud computing plays an important role and the second, the new opportunities offered by IoT devices capable of processing data, force companies to rethink their approach to IT infrastructure.
Edge devices collect, sort and analyze data and store the data in its intended location after processing.
“Edge Computing is an example of open distributed computing that ensures quick computation, manages data operations, network operations and data storage. This improves post time and saves bandwidth resulting in bringing devices closer to place. It has the power of decentralized processing to launch mobile computing and the Internet of Things. ”
Edge computing data is processed by the device or by a local computer or server without being transmitted directly to the data center. Data computing takes place at the edge of the device or where data is generated. Therefore, it significantly improves the speed of data processing by reducing the data that travels between devices and centralized cloud data centers.
This technology opens a platform to communicate on campus, where work is done in contrast to warehouses, retail stores, supermarkets, banks, etc. With the proliferation of the Internet of Things or IoT devices, there is a large chunk of data. In a centralized data center or cloud.
Therefore, it requires large and expensive connections to handle large amounts of data. The work done by these IoT devices creates the need for a faster connection between the data center or the cloud and the devices.
For example, at a petroleum refinery station, the valve’s sensor detects dangerously high pressure in the pipe. In that case, the shutdown for petroleum supply should be stopped immediately.
Automatic shutdown delays the shutdown process because it takes time to evaluate what is happening in remote processing centers. We can prevent this delay by keeping the processing power for local devices. This reduces latency, roundout trip time and saves time. Thus, humans, money and material suffer less loss.
A key component of cloud computing is maintaining security and balanced stability in the event of a failure in its connection. Even in the case of edge computing, these devices fall into various network elements and contain confidential data, which, in case of exploitation, may include valuable assets as well as other devices.
By building edge computing redundancy and providing failure conditions to prevent disruptions, Edge ensures that devices become a single point of failure network architect.
Edge computing devices include the Raspberry Pi 4B model, the Lotpanda Alpha, the Edu Bolt, the Jetson Nano (Nvidia) and the Intel Neural Compute Stick 2.
