Distributed architecture “edge computing” is attracting attention. Its characteristics, such as low latency (low delay), reduced network load, and enhanced security, are expected to solve IoT issues. 

It is used in many fields, such as manufacturing, agriculture, and retail. However, introducing edge computing is necessary to overcome cost and security measures. It is also essential to understand the benefits and standards correctly and work on them. This paper describes the overall picture of edge computing.

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What Is Edge Computing

Edge computing is a distributed computing concept in which data processing and analysis are performed by devices such as IoT terminals and servers installed near them. Since the data is cleansed, processed, and analyzed on the edge side without sending data to the cloud, it is highly real-time. It can be less prone to communication delays due to load distribution.

In contrast to the cloud, which centralizes data processing, edge computing can be said to distribute data processing.

Edge computing employs a distributed architecture mechanism, but it is not incompatible with the cloud, which centrally manages data. As shown in the diagram above, data is quickly processed by devices and edge servers. Only the necessary information is sent to the cloud via the network for accumulation and management. This enables both low latency and centralized data management. Can.

In the conventional IoT, a centralized system that transmits data collected by sensors to the cloud via the Internet and analyzes and analyzes was standard. In contrast, edge computing realizes real-time and low-load data processing by distributing data processing on the device itself or an edge server installed between the device and the cloud.

Why Edge Computing Matters

Load On Network

The first issue with IoT is the “load on the network.” IoT constantly sends large amounts of data to the cloud and data centers. The best example is the “digital twin,” a technology reproducing real space in cyberspace and predicting the future based on information sent from sensors.

Sending and receiving such a large amount of data puts a massive load on the network, so the more IoT is used, the more the cost of network maintenance and management will increase.

Large Latency

The second problem with IoT is the “large latency.” Latency is the communication delay time that occurs before data is sent. IoT requires a very high level of processing speed and response. Still, conventional IoT, which processes data in the cloud, sometimes causes a time lag of several hundred milliseconds to several seconds.

This time lag can lead to fatal IoT problems, requiring real-time performance.

Guarantee Of Security

The third challenge for IoT is to ensure security. Since IoT connects to the cloud via the Internet, the risk of being exposed to external threats increases. New security approaches such as zero-trust have been created to prepare for such risks in recent years, but securing security requires workforce and cost.

Benefits Of Edge Computing

Reduced Network Load

Edge computing is a new architecture that sends only necessary data to the cloud while performing high-speed and safe data processing on the edge side.

The first advantage of edge computing is the “reduction of network load.” After data processing is performed on the edge server, only the necessary data is sent to the cloud, reducing the amount of communication and reducing the load on the network.

Low Latency

“Low latency” is one of the most significant features of edge computing. Edge devices and physically nearby edge servers can significantly reduce delays in the data processing.

As the use of IoT progresses and a large amount of data continues to be sent from sensors installed in factories and buildings, a delay of a few milliseconds occurs when all the data is sent to the cloud server. For IoT products that require real-time performance, delays of even a few milliseconds can be a fatal problem, so measures such as storing and managing data in the cloud and rapid data processing using edge computing are taken. Real-time processing can be realized by taking.

One of the reasons for achieving low latency is 5G (5th generation mobile communication system). 5G is scheduled to implement ultra-high reliability and low latency (URLLC), and it is said that it can be applied to IoT, where real-time performance is critical, such as telemedicine and autonomous driving. In the future, it will be possible to operate robots in real-time using 5G at production sites such as factories.

Enhanced Security

Enhanced security is one of the advantages of edge computing. Since data processing is performed at the edge server without going through an external network, the risk of data leakage during data exchange can be significantly reduced.

Of the data processed by the edge server, only the data that needs to be stored and managed is sent to the cloud, reducing the network load and the risk of data leaks.

Promotion Of DX

Currently, DX is being promoted in each industry. In particular, the shift to DX in the manufacturing industry is inextricably linked to IoT. Edge computing plays a vital role as an architecture that enhances the real-time nature of IoT and will be indispensable in discussing future DX in the manufacturing industry.