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Home Technology Infrastructure & Platforms Computer, Storage, Networks, Connectivity

Appetite for private networks drives MEC spending

FutureCIO Editors by FutureCIO Editors
June 6, 2022
Photo by Dan  Nelson from Pexels: https://www.pexels.com/photo/woman-using-macbook-pro-3949100/

Photo by Dan Nelson from Pexels: https://www.pexels.com/photo/woman-using-macbook-pro-3949100/

According to new research from global technology intelligence firm ABI Research, the revenue for Multi Access Edge Compute (MEC) deployments for private cellular enterprise networks will reach US$5.8 billion by 2030. The so-called non-carpeted verticals like manufacturing, logistics energy generation, logistics, and healthcare show particular interest in MEC deployments.

MEC - Close to the user, at the EDGE!
Leo Gergs

“These numbers highlight the great momentum there is for distributed computing within private networks,” says Leo Gergs, senior analyst for enterprise connectivity and 5G markets at ABI Research, says distributed Computing offers great advantages to enterprise owners and operators of private networks both from a commercial as well as from a technical point of view.

As distributed computing allows the processing of payloads at different locations within the private networks, it reduces the strain on the cellular network core and therefore enables a smoother network performance.

Furthermore, in fully digitised enterprises, data will be generated in all possible different locations of the respective site. Distributed computing allows data to be processed much closer to their origin. “By reducing the transmission data between the place of origin and the place of processing, distributed computing drives down end-to-end latency, as any avoidable data transmit will be scrapped,” Gergs explains.

From a commercial point of view, distributed computing will allow for more economical network deployments, removing one of the most important barriers to entry for enterprises considering deploying a private network.

As distributed computing allows the offloading of certain processing capabilities to existing public infrastructure (e.g., a hyperscaler cloud), it will lower the total cost of ownership (TCO) by reducing the amount of dedicated infrastructure needed to be deployed on enterprise premises.

However, a certain level of dedicated infrastructure will always need to be deployed to preserve the integrity of each enterprise network.

According to Gergs, “Enterprises often transmit highly sensitive data – think about the condition of production assets, the conditions of a mine or the remote operation of cranes, for example. No enterprise owner is prepared to see this kind of data leaving the respective premises. As such, suppliers need to ensure that user plane data can always remain on-premises.”

As the distributed computing opportunity is vast, it will likely be the next wave of competition and innovation. “The spheres of influence are not yet set in stone, and the next few years will be pivotal for many established and new companies,” Gergs concludes.

Related:  Challenges and opportunities in edge machine learning adoption
Tags: ABI Researchhyperscalersmulti-access edge cloudprivate networks
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