What is Edge Computing?

 

Edge Computing, which is also called Fog Computing or Mobile Edge Computing (MEC), is a frequently used term in IIoT and refers to a new optimizing industrial data processing method. The place where computing and processing data, such as Cloud Computing, is not located in a remote data center. It is the model where computing devices are located in closed to the terminal equipment which is used by users. These industrial data and computing models are collectively referred to as “Edge Computing”. Although the devices existed in an area called ‘Edge’ in the past, their role was merely data transfer or some data storage.

However, the biggest difference between edge computing and older models is the ability to add computing capability to this ‘edge’ device to facilitate data storage and analysis in real time. With the rapid development of hardware technology, the decline in the price of processors and related chips and the increase in computation have made this high-performance edge computing possible. This allows the big volumes of data processing, large-scale data analysis and AI calculations, which could only be run on high-performance computers, to be driven by the edge equipment and is transforming into a main stream in many industries.

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Source : https://www.collaberatact.com/cloud-different-edge-iot-environment/

 

 

The Benefits of Edge Computing

 

There are a number of benefits that real customers can gain by leveraging edge computing, but we look into three benefits of edge computing in this article.

First, it can reduce data load and cloud costs. As the number of IoT terminals and the numbers of sensors increase, the amount and speed of data increases greatly. Hence, storing all of this data in the cloud is not a smart choice in terms of its cost and efficiency. It makes more sense to distribute the data processing by storing all the data for a certain period of time in the edge terminal and transferring only necessary data to the cloud.

Second, real-time response is possible. It is one of the most powerful advantages of the edge computing model. Analyzing all the data sent to the cloud and responding based on the result is far from the real-time model. Immediate analysis and response for the events occurring on the edge terminal and response are one of the main keys in the competitive business environment in  IIoT.

Third, it is relatively safe against security threats, which can ensure continuity of customer service. The public cloud is based on a wide area network (WAN). This is to take advantage of the service, taking care of a number of emerging security issues such as the DDoS attack. In particular, if you use cloud solutions for real-time response, such as in chemical industries or automobiles, you take various risk when the server is down for some reasons. However, the edge computing can prevent extreme situations such as service paralysis if the edge part device performs computing on a local area network (LAN) basis.

The Outlook of IoT Edge Computing

 

Currently, many services have been developed or still being developed, based on Cloud. However, due to the advantages of edge computing, it is expected that system development in IIoT will have more and more distinct boundaries between the cloud services and the edge. In particular, the edge will build a standardized form of its own software and hardware that can handle the large volumes of data and its storage. Of course, it should also be able to analyze all the data from sensors.

On the other hand, the cloud should clearly define the type and amount of data to be received from the edge. It is obvious that the actual operating costs of the cloud and its capability to process real-time data will serve as key decision points.

As the performance of the edge devices evolves, its AI and related analysis are expected to be activated. However, considering the constraints of computing power in the cloud services, the role of the cloud is still expected to remain important in the analysis and handling Big Data.

In the end, users should make an economic assessment of what combination of edge and cloud will reduce the business threats and minimize the cost. It is important to make a wise decision about whether to adopt Edge Computing from the process.

What is Edge Computing - explained by Solway Comms

Data flow in Edge Computing (https://www.solwaycomms.com/edge-computing/)

 

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