Edge computing is rapidly changing data collection, processing, and delivery. The growing demand for the IoT is one reason for driving the need for edge systems. Not only that, many business and industrial applications now need real-time computing. Fortunately, the rapid pace at which edge computing grows also derives steady support from network innovation such as 5G.
The global market for edge computing holds much potential. Many tech suppliers like Solid-Run are responding to the demand by offering tools and devices compatible with edge technology. At its most basic application, edge computing collects and processes data near the source. The purpose is to prevent latency, especially for use cases that require real-time responses.
What is the importance of edge computing and edge gateways?
For industries and companies that choose an edge gateway architecture, cost-effectiveness is enough reason. Eventually, they realize that edge gateways can collect, store, and process, data much faster. This functionality allows for the implementation of efficient and real-time apps. For example, if a business requires facial recognition for security, edge computing is faster. Instead of sending data to the cloud, the algorithm runs on the local server and guarantees faster response times.
The important role played by ARM gateways in edge computing
To understand better why edge computing has evolved rapidly, it’s essential to look at specific components that pushed this innovation. Since edge computing is the biggest trend along with AI and IoT, chip makers like ARM are designing new products that meet high-demand uses. An ARM gateway is necessary for edge computing simply because these chips are vital to developing more IoT-enabled devices. Thus, ARM will bring AI and edge computing to more devices that wouldn’t otherwise have this capability. For example, imagine an ARM-powered autonomous camera capable of detecting obstacles and using sensors to avoid them.
Indeed, edge computing applications are more demanding. As such, ARM processors can match this demand with better machine learning capabilities. There is more to look forward to in the future. Developers understand the need to choose the right topology when implementing edge gateways. ARM, because of its impressive processing power, is most compatible with AI and IoT use cases.
5G and wireless technology in edge computing
The deployment of 5G is another network innovation that will push forward edge computing. A faster network means better connectivity and decreased latency. In turn, companies will reduce cloud dependency when it comes to using applications. In turn, many will experiment and start using edge computing along with IoT-enabled devices.
As predicted by many tech experts, 5G is considered the catalyst to edge computing dominance. In relation to the demand for real-time applications, 5G is indeed laying the necessary groundwork for improved processing at the edge.
The essential role played by network technology and chip processing technology like ARM are all catalysts to edge computing. While edge gateways were initially seen only as a means of reducing bandwidth and costs, the current potential is more promising. As IoT improves, so does the need for enhanced edge processing and storage capability.