Edge Computing in Telecoms: Revolutionising 5G Networks

Edge computing has fast become a critical technology for 5G networks. It can not only help meet performance and low latency requirements, but also process data closer to the data source to reduce traffic volumes and business costs.

As the telecommunications industry continues to confront a new range of technologies, edge computing cuts out the middleman and processes edge data in real time. As a result, it is able to relieve pressure on the central network of a business.

We have already discussed how the telecommunications industry is in a prime position to capitalise on the latest advancements in technology, including generative AI (Gen AI). Read the full article HERE.

Taking this one step further, edge computing is expected to play more of an integral role in telecommunications transformation moving forward – providing the infrastructure required to make processing faster, reduce delays and save bandwidth. 

“Edge computing is a modern method of data processing that occurs at the ‘edge’ of a network, closer to where the data is generated, rather than being sent to a distant central server or cloud for processing,” explains Mark Cunningham, Head of Public Sector and Solution Sales at TalkTalk Business. 

“It is revolutionising the telecommunications (telecom) industry, allowing providers to improve service offerings and support emerging technologies.”

Preparing to boost 5G rollouts

Edge computing is a priority for many telco service providers as they modernise their networks and seek new sources of revenue. As telecom companies look to improve the availability and reliability of their network services, edge computing is able to create a highly distributed network that is less reliant on regionalised cloud infrastructure. 

The technology is complimentary with 5G, reducing the round-trip distance between the device and the data centre by minimising latency. Combining 5G and edge computing can facilitate a smoother and more efficient user experience, especially when it comes to applications that require real-time data processing like augmented reality and smart cities.

“Edge architecture provides faster connections, essential for high-demand applications like real-time video streaming or remote healthcare,” says Erez Sverdlov, Vice President, Cloud and Network Services, Europe at Nokia. “It reduces the load on backhaul connections, allowing 5G networks to maintain consistent performance even under high demand. These attributes ensure that mobile services are resilient and consistently available to end users.”

Mark Toman, Client Director at BT Wholesale, adds: “Edge combines some of the best elements of cloud and on-premise deployments. By bringing compute power closer to end use cases through 5G, it supports the ultra-low latency connectivity required for new innovations such as VR/AR and AI. 

Lower latency, or a reduction to delays, is able to advance parts of a network like the Internet of Things (IoT), thereby speeding up the adoption of 5G. Making the network more reliable in this way can allow telcos to gain new revenue streams and reduce costs moving forward.

5G is being readily adopted, with telcos eager to roll the network out more widely. With the first 6G wireless standards expected by 2030, areas of the world like Europe are investing more in emerging technologies for the future of the telco sector. 

The UK in particular is already targeting modern industrial strategies to support sectors with the largest growth potential to avoid continued slow 5G uptake.

Read about how the UK connectivity market evolved in 2024 HERE.

It is no surprise then that edge computing is being touted as a solution to help telcos prepare for continued 5G rollouts.

“Edge computing shortens the distances data needs to travel – also known as the data transmission path. This makes it ideal for 5G networks which rely on weaker frequency bands that can only travel shorter distances,” comments Mark Cunningham. “It offloads data processing from central servers, easing the load on core networks and boosting efficiency. For businesses offering services like IoT solutions or smart cities, having computing power and storage at the network edge is a game-changer. 

“Edge computing meets the technical demands of 5G while unlocking new business opportunities.”

Likewise, the technology can enable telcos to more efficiently handle 5G data demands, whilst minimising backhaul costs and network congestion. Erez explains that this will only enhance user experience, which in turn will attract and retain 5G customers moving forward.

“Data and processing closer to end-users improve the overall customer experience,” he explains. “The more localised network scope enables faster diagnostics and network adjustments, leading to better troubleshooting, reliability and faster problem resolution.”

He adds: “AI-powered edge capabilities allow for predictive maintenance and personalised services, proactively reducing disruptions and addressing customer needs in real time. A localised approach, in general, provides telcos with new tools to optimise the customer experience, ensuring continuity and tailoring telecom services.”

Transforming telco service delivery

Whilst edge computing enables telecom providers to deliver hyper-personalised services to its customers, its workloads are often highly data-intensive, given that they are processing large amounts of real-time data from sources like IoT devices.

Managing such a high volume of data in real-time can inevitably strain network resources and lead to issues with bandwidth, as Mark Cunningham explains.

“This becomes even more challenging when the data is sensitive, such as personal information or confidential business data, which introduces security risks,” he says. “As telcos, we need to prioritise data security and develop robust encryption and compliance processes to ensure that sensitive data is protected at every stage.”

Edge computing also faces challenges in infrastructure cost due to the need for distributed nodes, complex security management from multiple data access points and scalability as demand grows.

Mark Cunningham comments: “One way to tackle these challenges is through effective software-defined network and device management. For example, a cloud-managed system can provide centralised control over all connected IoT devices, giving businesses real-time visibility into their network access and usage. This allows them to spot potential issues, like a failing device or unusual data patterns, and address them before they cause disruptions.”

There is still education required over what a network edge development actually involves. Whilst on-premise deployments can take significant time to implement, edge network deployments can be replicated from existing network configurations so businesses can be up and running faster.

In considering this, Mark Toman explains that it is the responsibility of providers to teach telcos the awareness of these deployments.

“As we see more use cases go live, it will become easier to prove how quick implementation can be,” he notes. “As today’s ecosystem is fragmented in nature, a fresh approach is needed where we bring the ecosystem together and deliver bespoke solutions for customers. 

“Strong partnerships will be essential to support the telco industry in moving to edge networks, with providers, partners and innovative brands needing to come together to produce seamless deployments.”  

Erez adds: “Telcos can address challenges with partnerships (especially with cloud providers) and container orchestration platforms like Kubernetes for resource automation and scaling.”

Confronting these challenges could mean that telcos can harness edge computing to improve accessibility for their customers in more remote areas too. These parts of the network are the furthest from central servers and are prone to higher levels of latency and slower internet speeds. Edge computing is versatile enough as a solution to allow computing tasks to spread across different layers of the network.

“Edge nodes in remote regions can improve network performance and reduce latency, making high-speed internet and mobile services accessible to underserved communities,” comments Erez. “For instance, in healthcare, edge supports remote patient monitoring and diagnostics.”

An edge computing revolution

Over the next five years, ahead of 2030, the demand for edge computing is only set to increase, particularly as AI and extended reality technologies increase with demand. 

Most anticipate the edge computing market to grow from US$2bn in 2017 to anywhere between US$15-28bn in 2025, according to STL Partners. With this in mind, as edge computing matures, its integration with other powerful technologies like AI could enable greater real-time analytics and personalised services across the telco sector.

“We’ve reached a tipping point where hypothetical situations and proof of concepts are fast becoming reality with deployments going live,” Mark Toman says. “As the market matures, future use cases are likely to come from many directions across different industries.”

He adds: “The ultra-fast connectivity and low latency that Edge can deliver will enable pioneering use cases such as VR headsets which allow builders and surveyors to analyse building sites without physically being there. With network Edge-based services, companies can now get full access to data via a cloud provider. They can collect and manage data, and then apply analytics to improve efficiency. This can be transformative for a business with multiple sites by helping to inform decisions.”

Telcos can then use edge computing to drive 5G-enabled applications like smart vehicles, industrial IoT and smart city infrastructure. 

“Edge will also support the offloading of complex processing tasks from smartphones and other devices,” Erez explains. “Standards development and privacy enhancements will further expand telcos' role in diverse industries, making edge computing a foundational component as AI-driven 5G applications grow.”

As more telcos around the world are expected to adopt multi-cloud strategies, they will offer greater flexibility and scalability for their edge infrastructure. This increased provision of services can only pave the way for boosted revenue streams, particularly for IoT solutions, gaming and AR/VR.

“From now to 2030, technology will revolutionise the telco industry. At the forefront of this is Edge Computing,” Mark Cunningham says. “The integration of AI with edge computing will enhance operational efficiency and enable advanced analytics, helping telcos optimise their networks and offer personalised services to customers. 

“We’re just scratching the surface, but adoption is set to accelerate and redefine industry capabilities.”

To read the full story in the magazine, click HERE

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