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Existing local and centralized cloud infrastructures cannot support the high computing needs of these powerful applications because they require low latency or data transfer delay to easily transport data and gain real-time access. To reduce latency and bandwidth usage and reduce costs, computing powers and processes need to be closer to the physical location of the data. Solution? Move computing power to local infrastructure on the “edge” of the network, rather than relying on remote data centers.
Exciting 90% of industrial companies will use cutting-edge computer technology by 2022, according to Frost & Sullivan, a latest IDC report (registration required), 40% of all organizations will invest in computer science last year next year. “Edge computing is necessary to enable the next generation of industrial revolution,” says Bike Xie Kneron, vice president of engineering for AI technology vendor. The future of AI and other automation technologies depends on a decentralized edge, he explained, connecting things to the Internet and other devices to networked nodes or implementing AI-enabled chips that can build algorithmic models autonomously.
“Edge computing is a complement to the cloud,” Xiek says. “Like the cloud, leading manufacturers need to acquire and apply knowledge based on data that will drive smart manufacturers and smart products.”
Manufacturing moves to the edge
The edge computing movement is the result of a maritime shift in manufacturing over the past two decades. Manufacturers, while making industrial products, electronic equipment, or consumer goods, have slowly but steadily moved to increase system and process automation and self-control to produce products, maintain equipment, and optimize all supply chain links. .
As manufacturers implement more sensor-based and automated devices, they generate more data than ever before. But often, from data-based devices to centralized systems, data sets are unlikely to grow rapidly, slowing down automation and making real-time applications inoperable.
Edge computerization allows manufacturers to make flexible choices about data processing to eliminate time delays and reduce bandwidth usage, as well as what data can be destroyed after processing, Xie says. “Manufacturers can quickly process data at the edge, send data to the cloud if it’s a bottle, or move certain data to the cloud if there’s no problem with latency and bandwidth.” Processing data closer to where it is used not only saves bandwidth and reduces costs, but also makes the data more secure because it is processed immediately.
IDC predicts that by 2023, more than 50% of new business IT infrastructures will be deployed than in corporate data centers, less than 10% by 2020.
An example of cloud-to-edge switching is Paul Savill, Lumen’s vice president of product management and services, a technology company that provides a cutting-edge computing platform. Lumen recently completed an installation in a million-square-meter factory. Savill says robotic systems from 50 different manufacturers are based on edge computing, “because they had to be within 5 milliseconds of latency to accurately control robotics.” The deployment provides secure connectivity from cutting-edge applications to robotics manufacturers ’data centers, which“ collect information in real time ”.
Savill, however, has long-term data storage and automated learning and analytics applications. Other larger workloads are processed in large data centers with “high computing power” so that huge amounts of data can be processed quickly.
“This chain from public clouds to the local computer to the edge is very important,” Saville says. “It allows customers to take advantage of the latest advanced technologies in a way that saves money and achieves tremendous efficiency.”
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