Mobile Edge Computing (MEC)

What is Mobile Edge Computing (MEC)?

Multi-access Edge Computing (MEC) formerly known as mobile edge computing is a type of edge computing that extends the capabilities of cloud computing by bringing it to the edge of the network. MEC was borne out of the ETSI (European Telecommunications Standards Institute) initiative that originally focused on placing edge nodes on the mobile network, but it has now expanded to include the fixed network.

Whereas traditional cloud computing occurs on remote servers that are situated far from the user and device, MEC allows processes to take place in base stations, central offices, and other aggregation points on the network.

By shifting a load of cloud computing to individual local servers, MEC helps reduce congestion on mobile networks and decrease latency, enhancing the quality of experience (QoE) for end-users.

Wikipedia Says:- 

Multi-access edge computing (MEC), formerly mobile edge computing, is an ETSI-defined network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network and, more in general at the edge of any network. The basic idea behind MEC is that by running applications and performing related processing tasks closer to the cellular customer, network congestion is reduced and applications perform better. MEC technology is designed to be implemented at the cellular base stations or other edge nodes and enables flexible and rapid deployment of new applications and services for customers. Combining elements of information technology and telecommunications networking, MEC also allows cellular operators to open their radio access network (RAN) to authorized third parties, such as application developers and content providers.

Examples of Multi-Access Edge Computing (MEC)

• Autonomous vehicle functions In the case of autonomous vehicles, MEC can be utilized to share information on road infrastructure, the position of other cars /animals, and weather conditions directly to the vehicles, instead of having to interface with central cloud servers. Combining MEC with AI/ML will allow autonomous vehicles to be aware of their surrounding situations in real-time. The low latency that MEC provides is critical for autonomous vehicles to operate safely, as vehicles cannot afford to wait for information to be processed in the cloud.

• Enterprise Mixed Reality (MR), Augmented Reality (AR) and Virtual Reality (VR) applications MEC in AR/VR can support remote workers conduct maintenance and repair tasks in the field. A MEC solution would provide an overlay of rich information related to a particular asset they are repairing on the field force worker’s display on a headset or mobile device. Today, 3D models are too heavy to render on the end devices and cannot be done in the cloud, as the latency is too high. MEC allows the processing of data and potential rendering of 3D models of the device, which allows digital twin models to be augmented on the view of the worker, as well as enable a remote expert to annotate the image/video being streamed from the headset or mobile devices in real-time, as well

• Cloud gaming and multiplayer gaming MEC would move the intensive compute/graphics processing from a dedicated gaming console, or a data center as cloud gaming grows, to the edge of the network. Gamers would have access to the same quality of the game from a thinner client, anywhere within the network’s coverage. For gaming studios and developers, since MEC provides extremely low latency, cloud gaming becomes a viable way of giving the wider audience access to high-end gaming experiences and potentially a new income stream when combined with a new subscription model.

• Real-time drone detection There is an increasing need for solutions that detect when a drone has entered a secure, geo-fenced zone and trigger necessary alarms/actions as defined by the security teams that manage the site. Airports, as seen by the Gatwick Airport drone incident in the UK in 2018, prisons and hospitals could be primary adopters of this technology, because they need to be able to respond to threats immediately, which is made possible through MEC. Using MEC would reduce latency for identifying a foreign drone and mapping its path to determine whether it’s approaching an exclusion zone. MEC keeps data from the drone closer to its source, reducing the time taken to react when there is a breach or a security threat.

• Video analytics There is increasing use of video surveillance in cities/enterprises, with data volumes growing, due to both the number of cameras and the quality of footage increasing. MEC enables local break out of traffic and analysis at the network edge, as opposed to routing the video traffic to central control for analysis. This allows the aggregation of video streams from different types of cameras and can enable other video analytics applications including real-time facial recognition, asset monitoring, and footfall analysis. MEC reduces the cost, volume, and time it takes to transport raw footage to the cloud/central server and allows for real-time triggers based on the analysis.

The future of mobile edge computing 

Mobile edge computing is still a nascent market. Its association with 5G and telcos’ unique ability to support mobility, combined with the significant longer-term potential size of the applications make MEC of strategic interest to Telcos.  

In order to capture future growth opportunities in MEC, telcos must build propositions in more than one area, where synergy will help drive an incremental benefit. This could be done through working with real customers across edge domains and identifying common requirements across use case domains and also collaborating with customers to focus on defining business models.  

Moreover, there are some key questions that telcos should ask themselves to enhance the benefits of MEC: 

• What are my existing areas of strength, and can MEC help augment these? 

• How can I align my chosen business model with my existing customer base and network infrastructure?

• How many use cases can my MEC infrastructure support?  

• How easily can I implement a given business model? 

• What is my appetite for risk? 

It’s likely that many telcos will take a modular approach in the short term, adopting a complementary business model for an initial deployment, expanding into further areas as demand becomes clearer and technology starts to prove its efficacy.

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