Home IIoT Why is Edge Computing attracting attention – What are the differences compared to the cloud and on-premises?

Why is Edge Computing attracting attention – What are the differences compared to the cloud and on-premises?

Edge Computing has been attracting a lot of positive attention, especially with the spread of IoT. Often, Edge Computing is considered the opposite of the cloud, but it is not. In this blog learn the differences between Edge Computing, the cloud, and traditional on-premises technology; why Edge Computing is attracting attention; and what benefits it has.

Overview of Edge Computing and Why it’s Gaining Attention

What kind of Edge Computing is attracting attention? Let’s take a look.

Definition and Concept of Edge Computing

Edge Computing is a distributed open IT architecture that performs processing at the edge of a computer network.

“Edge” in Edge Computing means the edge, or edge of a computer network. If the center of the network is a data center or the cloud, the IoT devices – such as smartphones and tablets – are operating at the edge and are connected to the internet. By processing data near these edges, it’s possible to present the load from concentrating on network paths and data centers. Because of this, there is less latency and more efficiency when processing data.

Edge Computing is said to be characterized by its distributed processing capabilities. Instead of sending data to distant data centers, Edge Computing processes data on the device itself, or on a computer or server located close to the device. The purpose is to distribute the load and minimize communication delays by processing data nearby.

Why Edge Computing Matters

“Keeping your data close” is becoming increasingly important, but why?

As the amount of data communication increases, real-time data is becoming more and more important.

Amid the IoT era, the amount of data handled by various devices is increasing explosively. With that being said, the required processing speed and response are also increasing. A large-scale data center is required to handle a sizable amount of data, but it is more efficient to centralize processing at one location rather than have data centers at each location. This is one of the reasons why cloud computing has become popular.

However, it is inevitable that there will be some time lag when sending data to the cloud via the Internet, processing it, and returning it.

Sensor technology for robots and industrial equipment is evolving every day, and it is now possible to accurately capture a situation at any moment. However, if there is a time lag between data processing and response, sophisticated sensing technology will become meaningless.

High-precision IoT is required for devices that perform precise and complex movements. To respond to this, it is necessary to exchange information and data as close to real-time as possible. Edge Computing, which makes this possible, is attracting attention as a technology necessary for IoT to move to the next stage.

Difference from MEC

In recent years, MEC (multi-access edge computing) has emerged as a new form of Edge Computing.

MEC is an evolution of Edge Computing for mobile communications and has attracted attention as a great tool for 5G utilization.

5G is a communication standard that meets the requirements for large capacity, high speed, low latency, and multiple connections. By combining this with Edge Computing, network load can be distributed and reduced, and the performance of 5G can be further leveraged.

The role of the edge as seen from data processing methods. Differences from cloud and on-premises

So, what exactly is the “edge” in edge computing? As mentioned earlier, the purpose of Edge Computing is to eliminate delays in data processing responses and improve real-time performance. For that reason, critical information is distributed and processed at the “edge”, which on-site, rather than in the cloud.

For this reason, it is sometimes thought that Edge Computing has the opposite nature to cloud computing, which is a centralized processing type. But in the true sense of the word, cloud is contrasts with on-premises.

So, how does Edge Computing differ from traditional on-premises?

Edge Computing does not process all data on-premises. By separating what can be done at the edge from what should be sent to the cloud, makes it possible to maximize the benefits of each.

When a large amount of data needs to be processed accurately, or information that requires more real-time processing, it is done at the edge, or on-premises. Information that requires large-scale collaboration and aggregation, and is less affected by processing speed, can be managed smoothly by using the cloud. Because of this, it can be said that the original form of Edge Computing is “to accurately divide the roles of where to process information”.

5 Benefits of Edge Computing

What are the specific benefits of Edge Computing? The following five benefits outline the advantages of leveraging Edge Computing.

  • Low latency: real-time data processing

When accessing the cloud, there is typically a time lag between the time the data is sent and the time it is processed and received. This time lag – or communication delay time – is known as latency. With Edge Computing and distributed processing, latency is reduced. This reduces delays in data exchange and enables real-time data processing.

  • Traffic optimization and stabilization

The evolution and spread of IoT will further increase the amount of data communication in the future. There are predictions that there will be “data congestion” in communication routes and data centers if all of this data is aggregated in the cloud. Data congestion not only creates delays in data transmission and reception but also carries the risk of causing failure in cloud services.

By using Edge Computing, organizations can reduce the amount of communication by not sending all data to the cloud and processing critical data at the edge. This also helps reduce pressure on network bandwidth.

Optimizing and stabilizing data traffic is one of the significant benefits of Edge Computing.

  • Reduction in communication costs

When transferring a large amount of data to the cloud, the cost of data transfer will also increase because of the increase in communication volume.

Combined use of Edge Computing will lead to a reduction in the amount of data transferred to the cloud and the amount of communication, reducing communication costs.

  • Strengthen information security

Storing corporate and personal information in the cloud presents potential security risks, such as leaks or external attacks.

Edge Computing eliminates the need to send and receive data to and from the cloud when processing data at the edge, which helps reduce the risk of a data leak.

  • Business Continuity Planning

Edge computing can also be a BCP (Business Continuity Plan). What if you handle all your data in the cloud and that cloud service goes down? The businesses rely on that data could go out of business.

With Edge Computing, organizations handle critical data at the edge, meaning if the cloud service goes down, operations will continue.

Introducing Edge Computing should be a priority and part of a business continuity plan for recovery and continuation in the event of an emergency.

There are many advantages to leveraging Edge Computing. The key is figuring out where and how you can benefit the most.

Current Issues of Edge Computing

While the use of Edge Computing brings a variety of benefits, there are some hurdles that must be overcome. To maximize the effectiveness of edge computing, the following issues must be resolved.

Balance between throughput and capacity

Edge Computing can speed up overall processing, but organizations must take countermeasures if their device’s processing power does not support it.

Increasing the processing capacity of edge terminals will cause higher power consumption, which will then lead to the need for larger terminals and heat countermeasures. These increase the cost from introduction to operation, and if the processing volume is increased later, it may be necessary to replace the equipment.

If you don’t find the balance between the amount of processing at the edge and the processing power of the terminal, it may end up being inefficient.

Strengthening multifaceted security

While reducing the amount of communication to the cloud decreases security risks, one challenge organizations face is an increase in the number of places where security must be maintained because of the distribution type.

When Edge Computing is introduced and networked at multiple sites, multifaceted security enhancement is required.

Delay due to data transmission/reception path

To ensure enhanced real-time performance with Edge Computing, it’s necessary to have a mechanism in place to determine whether organizations should distribute data to the edge or the cloud.

If the settings related to this sorting decision are not optimized correctly, there’s a possibility a detour will occur, such as issuing a command to the device via the cloud after processing at the edge.

The design of the data communication path, processing location, and command transmission method is crucial.

Initial cost associated with Edge Computing

To operate Edge Computing efficiently, organizations need to install terminals and servers as well as systems and personnel to manage those terminals, which can be costly.

The initial cost of preparing these items can actually be quite high. It’s important to compare the benefits of Edge Computing with the cost of investment to determine the value for your company.

Use Cases of Edge Computing

Edge computing is used in the following fields and places.

Abnormality detection of equipment operating in factories

Experienced management make intuitive decisions on maintenance of equipment and devices used in factories, as well as predictions moving forward based on past data.

In many production fields, preventive or predictive maintenance is becoming more and more popular, although it can occasionally create waste. For example, sometimes a part is replaced pre-emptively even though it can still be used. Other times, a part breaks down and is no longer usable when it was thought to still be ok.

Edge Computing plays an important role in minimizing deviations from such predictions and increasing the accuracy of maintenance.

Sensors attached to the equipment detect signs of failure and notify maintenance. A mechanism is used to judge the specific sound emitted by the device, the magnitude of the vibration, etc.

Edge Computing platforms collect sound and vibration data from sensors, the data is sent to the cloud, and big data analysis detects anomalies. Once patterned, the data that shows signs of anomalies are fed back to the edge, notifying those on site.

Inspect quality with image analysis

In manufacturing, specifically the processes leveraging precision equipment, there is a mechanism that uses an image processing system that determines whether solder processing is being performed properly.

When doing the work manually, the finished product often differs slightly from worker to worker but must fit within the standard values. By analyzing the camera images, the product is judged. If it is out of the standard range, the administrator is then notified.

Edge Computing is leveraged as the mechanism both judging and notifying.

Automatic parts supply system by AGVs (automated guided vehicles)

Automated guided vehicles (AGVs) supply the required parts needed in manufacturing plants at specific times. Conventional AGVs travel along routes determined by magnetic or optical tapes laid on the floor. Although extremely useful, it’s difficult to change the factory layout, hindering flexible responses to production plans.

By utilizing Edge Computing and 5G, the AGV can move along a set route with no tape needed as a guide. It calculates its own position by using sensors, automatically avoiding obstacles and potential collisions.

When the sensor detects a shortage of necessary parts on the shelves near the worker, the AGV automatically reads the barcode or IC tag and supplies the parts to the specified location. AI is also used to learn the work status and behavior data of the AGV, and that improves the accuracy of transportation.

Edge Computing and 5G are being used to communicate and process this critical data.

A smart factory that operates using all kinds of data

The purpose of smart factories is to collect data from every device in the factory and make full use of IoT to streamline operations.

Besides the operation of equipment, we collect all data, such as the movement of people on the production line, the status of transport equipment, and the inventory status of warehouses, and connect this critical information and use it for optimization.

Smart factories handle a huge amount of information, but communication delays can lead to production cycle delays and defects, which directly leads to lower production efficiency.

For this reason, introducing Edge Computing everywhere prevents delays and maintains stable operation of devices that operate in units of 0.1 seconds, 0.01 seconds, and even less.

Future industries supported by Edge Computing

In this blog, we introduced what Edge Computing is as well as what organizations can attain by leveraging it. As IoT becomes more important across industries, there has been an increase in expectations and attention to Edge Computing opportunities. Edge Computing platforms are an essential tool in supporting IoT growth.


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