Edge Computing: Optimizing IoT Networks for Speed and Automation

Looking over a canyon rim, turning a sharp curve, and approaching an unknown frontier: the edge of a moment provokes thought and discovery. New “edge” devices in IIoT and IoT systems stimulate operations the same way.

When computational system intelligence first began, power centralized in a single device that collected, stored and processed information. When the cloud became mainstream and virtualization common, the cloud held that central role and connected to devices.

In the past few years, large IoT providers, like IBM and Microsoft, have begun “distributing” the power of the cloud, architecturally shifting the system. Engineers pushed tasks, such as decision-making and analysis, from the center to the component parts of the network, its edge. This new format is known as “edge computing.”

These new IoT network systems are made of three parts: sensors and actuators, nodes and gateways, and the cloud. The sensors collect data being generated. The nodes, also called controllers, logically interact with sensors, transmitting their data and relaying commands to the actuator. Gateways are “hub” node devices that gather other controllers’ data and send it all to the cloud on one channel.

The sensors and nodes define “the edge.” These electrical devices start and end the network. They communicate the important information and carry out the tasks necessary to regulate an operation. They process data on-site. In fog computing, they also send data to the cloud for further analysis or storage while still locally processing.

Edge devices serve to optimize the IoT network. By communicating with gateways and using LPWAN technology, they reduce bandwidth consumption and reduce latency. They also send curated data sets rather than massive, indiscriminate data loads. Programmed to detect anomalies, edge devices prevent failure without ever receiving direction from the cloud. They increase security in some ways by limiting access points to the cloud. However, they do require more physical security and different access vulnerabilities. Using edge computing ensures real time data harnessing. They also can be low-power monitoring devices, saving energy.

As the data economy grows, access and usage of edge computing will become a substantial part of the market. By localizing action, edge machines quickly assess the situation and prompt faster discovery, a valuable part of operations. Understanding what edge devices do to expand operational potential, and seeking out the right edge network, is essential to having a share in that economy.