5G in edge computing: Benefits, applications and challenges

What is 5G edge computing?

5G edge computing is a paradigm in which computing, storage and network functions are placed closer to users or data sources, such as sensors, rather than being concentrated in remote data centers.

"5G is the wireless protocol that we use to transmit over our devices to a tower and ultimately base station," said Jack Fritz, principal in Deloitte Consulting's technology, media and telecommunications practice. He added that combining 5G with edge technology brings more computing power to users' wireless applications.

A key architectural model under 5G edge computing is multi-access edge computing (MEC), sometimes called mobile edge computing. MEC is defined by telecom standards-setting bodies European Telecommunications Standards Institute and Third Generation Partnership Project to provide an IT service environment, including computing, storage and network at the edge, enabling applications and services to run there with less latency, improved bandwidth efficiency and more control over where data is stored. MEC also supports multiple access technologies, including cellular, Wi-Fi and other technologies, so it is not limited to just one kind of network link.

The 5G standard contains specifications for how to support edge computing in the 5G core -- that is, a 5G network's central control and management software -- as well as the radio access network. The architecture generally involves the following:

• Edge application servers deployed at edge nodes to host applications and services.
• Edge enabler clients, which reside on user devices and communicate with edge enabler servers so that the device can discover and connect with edge services.
• User-plane function, which plays a key role in data transfer and packet processing, enabling traffic to be broken out or anchored locally so that data doesn't always have to travel back to core network servers.

Key components

Edge computing typically involves several components, including the following:

• Edge devices. These are the actual endpoints generating or consuming data. Examples include IoT smart sensors, cameras, vehicles, smartphones and robots that connect to edge nodes for processing.
• Edge nodes and servers. These include local computing units deployed at cell towers, base stations, on-premises sites or regional data centers. They host applications and perform data processing near the source.
• Network infrastructure. This connectivity layer includes 5G base stations, small cells, routers and switches that link devices to the edge and the cloud, ensuring low-latency data transport.
• Virtualization and containerization platforms. These include technologies, such as Kubernetes and virtual machines, that enable multiple applications to run securely and efficiently on shared edge infrastructure.
• Edge orchestration and management systems. These tools and platforms handle application deployment, workload migration, monitoring and scaling at distributed edge sites.
• Security services. These services include encryption, authentication, access control and threat detection, protecting edge nodes and connected devices. Edge security must be able to cover distributed environments.
• Cloud integration layer. This layer of interfaces links the edge with central cloud data centers for coordination, backup and large-scale analytics.

Benefits of 5G in edge computing

When 5G networks are paired with edge computing, applications can operate with faster responsiveness, higher reliability and greater efficiency than with traditional cloud models. The 5G-edge combination also supports real-time decision-making, enables more immersive experiences and provides the infrastructure for industries such as healthcare, transportation and manufacturing to innovate at scale.

Among the benefits of 5G edge computing are the following:

• Lower latency. Because processing happens near the device rather than in faraway cloud servers, response times are drastically shortened. This makes applications like augmented reality (AR), virtual reality (VR), remote surgery and autonomous vehicles feasible, since even milliseconds of delay can make the difference between success and failure.
• Bandwidth efficiency. Not all raw data needs to travel across the entire network. Edge computing enables filtering, compression and preliminary analysis to occur locally, which reduces network congestion and cuts transmission costs.
• Reliability and resilience. Edge nodes can continue operating even when connections to central clouds are weak or disrupted. This local independence helps ensure that critical applications, such as factory automation and emergency services, remain available.
• Enabling new applications. By supporting real-time analytics and interaction, 5G edge computing makes it possible to deploy advanced use cases such as smart cities, connected healthcare, immersive gaming and industrial IoT.
• Data privacy and security. Processing sensitive information at or near its source helps organizations comply with data sovereignty laws and reduces the risk of exposure during long-distance transfers.

"From the context of the cyber side, I can now have a resilient network using 5G and AI," said Dave Krauthamer, field CTO of QuSecure, which makes a post-quantum cryptography platform. "One of the elements we have is the ability to enhance the cryptographic fabric in real time based on threat patterns."

Applications of 5G in edge computing

Among the applications that take advantage of the responsiveness, reliability and efficiency of 5G in edge computing are the following:

• Autonomous vehicles and intelligent transport. Edge nodes near roads can process sensor and camera data in real time, enabling safer navigation, collision avoidance and vehicle-to-infrastructure communication with very low latency.
• Smart manufacturing. Factories use 5G edge computing for robotics coordination, predictive maintenance and real-time quality control by processing data from sensors and cameras directly on-site.
• AR and VR. Immersive applications for training, remote assistance and entertainment rely on 5G edge to minimize lag and provide smooth, real-time rendering.
• Healthcare and remote medicine. Wearables and connected devices stream patient data to local edge nodes for instant analysis, while telemedicine and even remote surgery benefit from the ultra-low-latency connection.
• Smart cities and public safety. Video analytics for surveillance, crowd monitoring and traffic management are conducted at the edge to deliver real-time insights for urban efficiency and safety.
• Retail and customer experience. Edge computing enables cashier-less checkout, personalized offers in real time and AR-based shopping experiences in physical stores.
• Energy and utilities. Smart grids and remote asset monitoring take advantage of 5G edge for real-time balancing, outage detection and predictive maintenance of energy infrastructure.
• Logistics and supply chain. Edge-enabled tracking helps companies monitor fleets, shipments and warehouses in real time, improving efficiency and reducing losses.

Challenges of 5G edge computing

While 5G edge computing offers powerful capabilities for real-time processing and advanced applications, it also faces the following hurdles:

• High deployment costs. Building out distributed edge infrastructure, such as servers, nodes and localized data centers, requires significant capital investment and ongoing maintenance.
• Complex infrastructure management. Coordinating workloads across many small, distributed sites is far more complex than managing centralized cloud infrastructure.
• Interoperability issues. Different vendors and standards can create compatibility problems, making it harder to ensure smooth integration of devices, applications and networks.
• Security and privacy risks. With more distributed points of processing, the attack surface expands. Ensuring consistent security across edge nodes is a significant challenge.
• Latency variability. Although edge computing reduces latency, real-world conditions like network congestion and user mobility can still cause delays and disrupt service.
• Skills and expertise gaps. Designing, deploying and managing 5G edge products requires expertise in telecommunications, IT and cloud-native software -- skills that are still scarce in the workforce. For this and other reasons, the powerful combination of 5G and edge computing still has a way to go before reaching its full potential in real-world applications.
• Uneven deployment of 5G. Similar to the latency issues, the uneven deployment of 5G in the U.S. and other parts of the world can create disincentives for developing edge applications that rely on ubiquity.

"It feels like the handset carriers or even the networks on which these handsets run are probably being disingenuous, where you see 5G show up on your phone and there is no 5G," said Thomas Pace, co-founder and CEO of cloud security company NetRise. "On paper, the benefits are low latency, high bandwidth, better reliability -- all that stuff. Those are all the promises of 5G. I am not seeing them."

Cynthia Brumfield is a writer, analyst, publisher and instructor specializing in cybersecurity. She is the author of the Wiley book, Cybersecurity Risk Management: Mastering the Fundamentals Using the NIST Cybersecurity Framework.