The current local and central cloud infrastructure cannot support the massive computing needs of these powerful applications, which require low latency – or data transfer delay – to seamlessly move data and gain real-time access to it. To reduce latency and bandwidth usage, as well as curb costs, computing power and operations need to be closer to the actual location of the data. The solution? Transfer computing power to the local infrastructure at the “edge” of the network, rather than relying on remote data centers.
enormous 90% of industrial establishments It will use cutting-edge computing technology by 2022, according to Frost & Sullivan, while Prof. The latest IDC report (Registration required) It was found that 40% of all enterprises will invest in advanced computing within the next year. “Advanced computing is essential to enable the next generation of the industrial revolution,” says Baek Zeh, vice president of engineering at Kneron, the artificial intelligence technology company. It shows that the future of artificial intelligence and other automation technologies depends on the decentralized edge, whether that’s by connecting IoT and other devices to distributed network nodes or implementing AI-powered chips that can build algorithm models independently.
“Edge computing is complementary to the cloud,” says Xie. “Like the cloud, edge technology enables application manufacturers to acquire and apply data-driven knowledge that will power smart factories and products.”
Manufacturing is moving to the edge
The move towards advanced computing is the result of a major change in industrialization over the past two decades. Manufacturers, whether they manufacture industrial products, electronic equipment, or consumer goods, have slowly but surely shifted to increasing automation and self-monitoring of systems and processes to increase efficiency in product production, equipment maintenance, and optimize every link in the supply chain.
As manufacturers use more sensor-based and automation-based devices, they are also generating more data than ever before. But all too often, data sets from sensor-based devices to centralized systems can quickly become impractical, slowing automation and rendering real-time applications inoperable.
Edge computing allows manufacturers to make flexible choices about data processing to eliminate time lag and reduce bandwidth usage, as well as data that can be destroyed directly after it is processed, says Xie. “Manufacturers can quickly process data at the edge if moving data to the cloud is a bottleneck, or moving certain data to the cloud if latency and bandwidth aren’t an issue.” Not only does processing data close to where it is used save bandwidth and reduce costs, but data is more secure because it is processed instantly.
IDC predicts that by 2023, more than 50% of new enterprise IT infrastructure will be on the edge rather than corporate data centers, up from less than 10% in 2020.
An example of switching from cloud to edge comes from Paul Saville, senior vice president of Product and Services Management at Lumen, a technology company that offers a cutting-edge computing platform. Lumen recently installed in a brand new one million square feet plant. The robotic systems from about 50 different manufacturers rely on advanced computing “because they needed to be within 5 milliseconds of latency for precise control of the robots,” says Saville. Deployment provides a secure connection from high-end applications to robot manufacturers’ data centers, “where they collect information on a real-time basis.”
But for long-term data storage and for machine learning and analytics applications – it’s all in the public cloud, Saville says. Other large workloads in large data centers are handled with a “colossal computing power” that can process massive amounts of data quickly.
“This chain from public cloud to offshore computing to workplace is very important,” says Savill. “It gives customers the ability to benefit from the latest advanced technologies in a way that saves them money and delivers tremendous efficiency.”