What is mobile edge computing?

Multi Access Edge Computing vs Mobile Edge Computing

What are examples of multi access edge computing (MEC) use cases?

There is no “killer app” for multi access edge computing; it’s being considered under a range of use cases. MEC improves the speed of established applications like content delivery and caching, but it’s also enabling new ones. MEC will create new revenue-generating (5G) use cases and possibly increase telecom efficiency in providing high-throughput content. MEC helps consumers and telecoms.

Vehicle connectivity/autonomy MEC may be used to communicate information about road infrastructure, pedestrians/other cars/animals, and weather conditions directly to autonomous vehicles, instead of central cloud servers. MEC with AI/ML will provide autonomous cars real-time situational awareness. Autonomous cars cannot wait for cloud-processed information to function properly, therefore MEC’s short latency is crucial.

Enterprise MR, AR, and VR apps

AR/VR MEC can help remote employees do maintenance and repairs. A MEC system would overlay rich asset information on field workers’ headsets or mobile devices. 3D models are too heavy to render on end-devices and the cloud has too much delay. MEC permits processing of data and rendering of 3D models outside the device, allowing digital twin models to be superimposed on the worker’s perspective and a distant expert to comment the image/video streaming from the headgear or mobile devices in real-time.

MEC enables multi-user MR collaboration for AEC teams. Real-time collaboration is enabled by rendering models on the edge cloud. This minimizes delay, since 3D files are frequently large. MEC deployment offers simple sharing through a dispersed network.

Multiplayer cloud gaming

MEC would relocate demanding compute/graphics processing from a game console to the network edge. Gamers may play the same game from a thinner client wherever in the network’s range. MEC’s low latency makes cloud gaming a feasible solution for studios and developers to provide a larger audience access to high-end gaming experiences and a new revenue stream when paired with a subscription model.

Real-time drone tracking

Solutions that identify when a drone enters a secure, geo-fenced zone and trigger relevant alarms/actions are needed. Airports, as evidenced by the Gatwick Airport drone incident in the UK in 2018, jails, and hospitals might use MEC since they need to react to threats promptly. MEC reduces latency for spotting a foreign drone and tracking its course to determine whether it’s nearing an exclusion zone. MEC keeps drone data near to its source, minimizing response time to security breaches.

Video analytics

Due to more cameras and better footage, cities/businesses are utilizing more video surveillance. Mobile edge computing permits local traffic break out and analysis at the network edge, rather than central control. This allows the aggregation of video data from several cameras, enabling real-time face recognition, asset monitoring, and footfall analysis. Mobile edge computing reduces the cost, volume, and time required to transport raw video to the cloud/central server and activates real-time analytics.

Mobile edge computing (MEC) opportunities, solutions and challenges

Opportunities for telcos in MEC

MEC offers a wealth of vertical and horizontal use cases, but telecoms face a more challenging situation. Telcos might theoretically:

• Improve network operations to achieve efficiencies and cost savings
• Differentiate own service offerings through MEC capabilities
• Enable others to make use of distributed compute capabilities
• Provide new applications and solutions using MEC capabilities

Telcos want to employ MEC to develop new revenues as core connection ARPUs decrease and voice and data become commodities. MEC’s business models are outlined here. In MEC, a one-size-fits-all strategy may not work since each application domain has distinct demands. Our webcast Edge computing from the front line: developer case studies highlights some of them.

MEC telco business models

Telcos shouldn’t wait for mobile edge computing to develop before pursuing commercial possibilities. With competition approaching, they should develop financial structures to support MEC use cases.

We have defined five telco business models:

• Dedicated edge hosting
• Edge IaaS/PaaS/NaaS
• Systems integration
• B2B2x solutions
• End-to-end consumer retail applications

A telecom may pick from a menu of risk- and capability-based business models. Telcos have an opportunity as first-movers in MEC, but they must find use cases and provide platforms for developers to exploit MEC infrastructure.

Challenges of mobile edge computing for telcos

Although Telcos may use numerous business models to leverage MEC’s economic prospects, they must first overcome certain significant issues.

• Security challenges: Distributed cloud poses a security risk. Stricter data protection and sovereignty standards may diminish MEC’s perceived desirability because of security problems.
• Commercialisation: It’s uncertain which telecom edge use cases will benefit carriers and consumers. Telcos must choose a value chain sector based on their expertise and offerings.
• Operationalisation: Different telecom parts see edge computing differently for internal/external use cases and NFV and 5G projects. Some telcos use edge capabilities internally to assist 5G rollouts, while others see it as a by-product of 5G, which requires distributed computation regardless.

Competition from hyperscale cloud providers

Amazon Web Services and Microsoft Azure are going to use edge and expand their centralised cloud services via Greengrass and Outposts (from AWS) and Azure Stack and IoT Hub. Several developments cause organizations to employ local and distributed computation and storage, including:

• The growth of IoT apps that produce amounts of data that don’t need to be handled centrally.
• Advanced cloud platforms support distributed computation models via hybrid cloud (e.g. Azure Stack) or serverless computing (e.g. AWS Lambda).
• Chip technologies that execute computing operations efficiently on extremely little physical area – for low-performance applications (e.g., “system on a chip” architecture on mass IoT devices) and high-performance applications (e.g. through modern Graphics Processing Units for AI-dependent use cases such as autonomous cars).

Mobile edge computing market size

MEC is considered a medium-term potential for telcos, since it will take time for application developers to take use of the necessary infrastructure. The global map below illustrates that most telcos have only begun rolling out MEC sites.

Despite variations (upper/lower limits) in forecasts from many sources, the worldwide MEC market will increase significantly in the next several years.

This increase will be driven by telecoms deploying MEC infrastructure in 2020 and MEC applications across sectors.

Next steps for telcos – The future of mobile edge computing 

MEC’s relationship with 5G and telcos’ unique capacity to enable mobility, together with the applications’ long-term promise (AR/VR, drone control, etc.), make it of strategic relevance to Telcos.

Telcos must construct offers in several areas where synergy can provide additional advantage to exploit future MEC growth prospects.

This may be done by engaging with actual customers across edge domains to uncover common needs and by cooperating with customers to define business models.

Telcos should ask themselves these questions to improve MEC:

• Which of my strengths can MEC bolster?
• How can I connect my business strategy with my customers and network?
• My MEC infrastructure supports how many use cases?
• Is a business model easy to implement?
• Risk tolerance?

Many telcos will likely take a modular strategy in the near term, choosing a complimentary business model for an initial rollout and expanding as demand grows and technology proves itself.

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