MEC, or multi-access Edge Computing, utilizes 5G technology, which is bringing a lot of positive attention. Although it’s gaining traction, many don’t understand the difference when compared to conventional Edge Computing. Within this blog, we’ll introduce use cases and specific examples.
What is MEC
MEC is an abbreviation for Multi-Access Edge Computing and is one standard developed by ETSI (European Telecommunications Standards Institute). The technology evolved Edge Computing for mobile communications and is rapidly gaining attention as a great way to tap into 5G network performance.
What is Edge Computing
Edge Computing is a distributed computing model deployed in OT environments close to critical equipment or processes – where data is being collected and analyzed – rather than on a centralized server or in the cloud. By processing data close to equipment, analysis is performed at high speed and at low latency.
It is often used in applications that require high real-time performance, such as autonomous driving and factory robots.
For a more detailed explanation of Edge Computing, please read “Why is Edge Computing attracting attention? What is the difference between cloud and on-premises?”
What is the difference between MEC and Edge Computing
MEC is an Edge Computing technology centered on communication from mobile devices, such as 5G terminals and IoT devices in the local environment. MEC was developed with mobile communication in mind.
Conventional Edge Computing is a network computing technology that processes and analyzes data at the edge terminal itself or at a computer placed near the terminal. Among edge computing technologies, MEC differs as it is a standard that considers mobile communications.
Background of MEC attention
5G is a wireless communication standard that achieves ultra-high-speed communication (eMBB), ultra-low-latency communication (URLLC), and multiple simultaneous connections (mMTC). It’s important to rethink the overall network architecture so that we can take full advantage of 5G performance.
MEC was developed as a technology for that very purpose. By introducing MEC, network load reduction, low latency, and high security will be achieved.
For example, if VR (virtual reality) or MR (mixed reality) was introduced into customer service, it will be possible to provide a customer experience that makes them feel as if they are in that space, enabling the realization of unprecedented services. In this way, MEC is attracting attention as a technology for maximizing the capabilities of 5G communications.
Use cases for MEC and Edge Computing
Traditional Edge Computing is well suited for distributed processing of applications to reduce the time to send and receive data between terminals and servers.
This is because it can reduce the amount of data sent to the cloud server by performing primary processing on the data sent from the terminal. Organizations achieve end-to-end low latency by utilizing Edge Computing.
MEC is well suited for improving network latency and security in mobile communications. This is because organizations install it using UPF – a network function that facilitates the operation of the user plane – which is the data transfer route. Introducing MEC makes it possible to process data on a local network. For example, by combining MEC with 5G, it can be used for the following purposes.
For example, by combining MEC with 5G, organizations can leverage it for the following purposes.
- Autonomous driving
- Autonomous robot
- Video analysis
- VR (augmented reality), MR (mixed reality)
The more MECs you install, the more efficiently you can send and receive data. It should be noted that it is necessary to carefully determine the number of MECs and their installation locations when considering business model constraints, including costs.
Examples of MEC utilization
MEC is attracting attention as a technology that brings out the performance of 5G, but how is it being leveraged in the manufacturing industry? Below, find an interesting use case.
Application example for automatic transport system for warehouse logistics
Here’s an example of using MEC in an automatic transport system in a large warehouse.
This company had already introduced autonomous mobile robots in the warehouse, but in order to operate autonomously, it was necessary to load one control unit onto each robot. Unfortunately, the cost of introduction and maintenance was high.
By introducing a local 5G network and MEC in the warehouse and merging the control unit, the company reduced the cost of moving the robots into the warehouse to transport robots with only a distance sensor and a motor.
In addition, by utilizing 5G, which realizes low-latency communication, it became possible to control each transport robot in real time.
As a result, a single type of robot can transport loads of different sizes. The company has successfully developed a low-cost and flexible transportation system.
Use cases for remote work support on production lines
This use case showcases the use of smart glasses and 5G/MEC for remote work support and a system that efficiently delivers instructions to multiple workers.
On the production line of this factory, images are taken by workers wearing smart glasses and are sent to the MEC in real time. AI immediately processes those images, making it possible to call attention to what is happening in front of workers and to the support instructors. Not only can support for workers be carried out by a small number of people, but quick troubleshooting is also made possible.
In addition, as AI is installed in the MEC, it completes video analysis within the local network. This eliminates the need to send videos of the production line to the cloud, reducing security risks.
Assembly work demonstration experiment supported by AR
Below, find a demonstration experiment using 5G and MEC for assembly work instructions using AR.
This company has developed a system that analyzes the assembly status – in real time – with AI. The system provides instructions via AR by taking pictures of the hands assembling parts with a camera and then transferring large-capacity images to MEC via 5G communication.
They used projection mapping, leveraging a projector for AR.
If the parts are assembled incorrectly, the system displays the error immediately so that the worker notices the mistake.
If there is no problem with the analysis results, projection mapping displays the next action, and the worker can assemble the parts efficiently.
This system uses 5G wireless communication to transfer images to the MEC, so they can move the camera and projector that shoot the hands anywhere within the network. This makes it possible to build a flexible and proficient production line.
Choosing between MEC and Edge Computing according to your needs
As mentioned above, Edge Computing is a network technology that reduces traffic on cloud servers by collecting and processing data at locations close to data sources, such as sensors and devices.
MEC is an evolution of Edge Computing for mobile use. MEC is an essential technology for achieving ultra-low latency and top security in mobile networks.
If MEC evolves, we will realize an ultra-high-speed, ultra-low-latency network that can perform computation immediately wherever data is generated. However, it is also important to note that MEC can be costly. Therefore, when using MEC for 5G, it is necessary to decide where to install the edge server according to the purpose.
Please refer to this article to deepen your understanding of MEC and how it can be used for your business.