Mobile Edge Computing: frequently asked questions

Mobile Edge Computing: frequently asked questions

We’ve been getting a lot of questions about mobile edge computing lately, so we decided to come up with an FAQ that covers the basics. So, without further ado,

What is Mobile Edge Computing?

Mobile edge computing (MEC), now more correctly called “multi-access edge computing,” is a distributed network architecture that moves processing, storage and applications closer to the “edge” telecommunications network.

“Edge” here refers to nodes of the network that are closest to the end user, i.e. the base stations, routers, switches, and so on. (In the extreme case, “edge” can refer to the user’s device as well, but that’s not the case for Mobile Edge Computing as it is standardized.)

What is the difference between edge computing and Mobile Edge Computing?

“Edge computing” is a broad term used to describe any computing that takes place outside of a data center. MEC, in turn, is a standard defined by the European Telecommunications Standards Institute. Having such a standard helps ensure compatibility between different vendors’ products and services, so that they can work together seamlessly.

How does Mobile Edge Computing work?

MEC is implemented by installing applications and services on edge nodes of a telecommunications network (e.g. EnodeB for LTE networks). So, instead of sending data to a central cloud server over thousands of kilometers, MEC deploys “local clouds” in the proximity of a group of users. This way, they can enjoy the benefits of a cloud infrastructure while reducing the latency to an almost negligible level.

What are the benefits of Mobile Edge Computing?

By processing data at the edge of a network, rather than in a central location, MEC can provide lower latency, energy consumption, and resilience against connectivity issues.

What are some use cases for Mobile Edge Computing?

MEC is beneficial anywhere where latency is a primary concern. Here are just a few examples:

  • Autonomous driving: MEC can be used to process data from sensors in real-time, reducing the latency between self-driving cars and their environment.
  • Manufacturing: MEC can be used to monitor and control industrial machines in real-time, improving safety and efficiency.
  • Virtual/augmented reality: MEC can be used to process data from VR headsets in real time, providing a more immersive experience for users.

MEC also provides improved data security, as the data isn’t shared over long distances.

Finally, MEC can work the other way round, offloading computationally intensive tasks from individual devices to the MEC server, reducing power consumption and battery demand.

What is the relationship between Mobile Edge Computing and 5G?

5G is the next generation of cellular technology that promises to be 20 or more times faster than 4G. An important part of the 5G standard is that it’s designed to support more than just phones.

5G will allow devices like sensors, cars and industrial machines to communicate with each other and the network. As a result, a lot of the compute-intensive tasks that currently take place on either the cloud or the device itself can be offloaded to the network.

This sounds a lot like our description of mobile/multi-access edge computing above. Indeed, MEC has been said to “enable 5G functionality on 4G networks.”

At the same time, MEC is not just about 5G. It can be implemented on any network, and it’s a much broader concept. As Alex Reznik of Dell puts it, “multi-access edge computing is much more about the Cloud at the edge — how to manage it, how to run applications on it, what services such a platform can offer,“ so, while “getting the traffic to and from it is essential, […] the rest of the system [is] agnostic to what ‘G’ you are on.”

Where can I learn more about Mobile Edge Computing?

ETSI’s website, specifically its MEC blog, is a great source of information on the latest developments in mobile/multi-access edge computing.

You can also check out the MEC Wiki, where you can find a list of MEC projects, use cases and other resources.Finally, if you have any questions, feel free to drop us a line at hello@edge.ai, and we’ll be happy to help you navigate the world of edge computing.

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