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Why Edge Computing Matters: Definition, How It Works, and Use Cases

Why Edge Computing Matters: Definition, How It Works, and Use Cases

Edge computing is changing the way we store, process, analyze and transmit data generated by billions of IoT and other devices. 

The initial goal of edge computing was to reduce the bandwidth cost of transporting raw data from where it was created to the corporate data center or cloud. More recently, however, the concept has evolved to support real-time applications that require minimal latency, such as autonomous vehicles and multi-camera video analytics. The worldwide proliferation of 5G wireless standards is closely related to edge computing as 5G will enable faster processing for these advanced low-latency applications.

Edge Computing Definition

Gartner defines edge computing as 'the part of a distributed computing topology where information processing is located close to the edge where information is generated or consumed'. 

At its most basic level, edge computing places computing and data storage close to the devices that collect it, rather than relying on central data centers thousands of kilometers away. By doing this, the data (especially real-time data) does not suffer from latency issues that can affect the performance of the application. In addition, enterprises can reduce costs by reducing the amount of data that must be transferred to a central data center or cloud base. 

Think of a device that monitors manufacturing equipment in a factory, or an Internet-connected video camera that transmits real-time video from a remote office. A single device generating data can easily transmit data over a network, but problems arise when the number of devices transmitting data simultaneously increases. Instead of a single video camera transmitting real-time video, consider hundreds or thousands of video cameras. Not only does latency degrade quality, but bandwidth costs can be astronomical. 

Edge computing hardware and services assist in solving this problem by providing the field with compute and storage resources for many of these systems. For example, the edge gateway may transmit only meaningful data to the cloud after processing data received from the edge device. If a real-time application is required, the processed data can be retransmitted to the edge device. 

5G and Edge Computing 

It is possible to deploy edge computing on other networks besides 5G, such as 4G LTE, but conversely, it is not always the right answer for enterprises to utilize 5G in addition to edge computing. In other words, it is difficult for enterprises to reap real benefits from 5G unless they have an edge computing infrastructure. 

Dave McCarthy, research director for edge strategy at IDC, said: “5G by itself reduces network latency between endpoints and base stations, but does not address the distance to the data center. This can be a problem for latency-sensitive applications.”