Edge Computing: Why It’s Crucial for 5G Networks 

Estimated reading time: 4 minutes

What Is Edge Computing in IoT 

Data collected from networked devices is often sent to centralized databases or servers and processed. The process may require transmitting information back to the devices, which causes issues, including: 

• Introducing latency 

• Crowding bandwidth 

• Compromising security 

Edge computing streamlines the flow of information to and from Internet of Things (IoT) devices. Data processes closer to the source — at the network’s edge — where analytics provide insights locally in real time. Core systems or networks are not strained.  

Edge processing enables companies to reduce traffic to centralized systems. It also lowers or removes latency in critical operations, such as manufacturing or health care, where every millisecond counts.  

In addition, edge computing also has the resiliency to continue operations if the network is unavailable. It improves security for many applications. Specific sensitive data processes on-site, not on a centralized system.  

Security is crucial in the era of GDPR and increased focus on protecting personal information. 5G promises data speeds up to 10 times faster than 4G. It will help simplify edge computing and may drive additional demand as new business models are enabled. 

What Is the Impact of 5G Networks on Edge Computing? 

5G networks will allow better real-time connections between edge devices and cloud-based servers with its:  

• Projected enhanced reliability  

• Significantly reduced latency 

• Bandwidth capacities in the gigabits  

The estimated market size of edge computing is expected to grow at a compound annual growth rate (CAGR) of 13% from 2023 to 2029. 

5G is currently in a market-driven phase. The market continues to add services and explore use cases, like satellite communications and mid-speed IoT NR RedCap. These will affect edge computing in the long run.  

The most significant impact 5G has had thus far is on enhanced mobile broadband (eMBB). This is especially true for high-speed data use cases requiring data aggregation and higher data throughput (e.g., video streaming).  

Telit Cinterion is launching its third generation 5G product for eMBB in the high-speed and mid-speed (NR RedCap) categories. It will be compatible with any edge computing architecture. 

Meanwhile, mobile and IoT technology is expanding at an ever-increasing rate. An analysis from zScaler shows that the global number of connected IoT devices will surpass 29 billion by 2027.  

Autonomous vehicles, streaming video and IoT devices will generate vast amounts of data. Given this escalation of data requirements, edge computing will remain a necessary stage in the transition to full 5G. The two are developing in tandem. Projections have the global edge computing market reaching $257.3 billion by 2025.  

Unlocking the Potential of 5G with Edge Processing 

The relationship between 5G and edge computing is mutually beneficial. Edge processing is necessary for the transition to higher speeds and greater bandwidth. Moreover, it’s essential for companies to maintain a competitive edge and keep customer and employee data secure.  

Intelligent investment in edge infrastructure (e.g., private LTE and private 5G) will build faster, more extensive mobile and IoT networks. Edge processing can translate data to secure protocols before sending it to the cloud. In addition, it can:  

• Reduce bandwidth requirements between the cloud and edge devices  

• Eliminate latency issues 

• Provide real-time analytics 

• Smooth the long, uneven transition to full 5G  

What may seem like an additional layer of complexity provides needed security and availability for emerging IoT networks. 

Moreover, the greater flexibility and scalability of network architectures today help trigger different ways of deployment. This enables architectures to support edge-intense applications like private networks for industrial and business use cases.  

On the computing side, AI brings far more processing capabilities to the edge. Enterprises can combine 5G’s ultralow latency with edge AI to improve real-time decision-making. By 2030, the edge AI market is projected to reach $62.93 billion at a CAGR of 20.1%. 

Succeeding at the Edge with Telit Cinterion  

Telit Cinterion has several offerings that tackle complex issues at the edge. OneEdge™, powered by Telit Cinterion, has module-embedded functionality. It pushes the burden of integrating new components to the edge by: 

• Improving security 

• Streamlining processes 

• Shortening the path to market for new IoT applications  

deviceWISE®, powered by Telit Cinterion, is an award-winning IoT platform that enables rapid integration between industrial assets (e.g., PLCs, CNCs and SCADA systems) and cloud systems. Our deviceWISE AI offering enables high-performance visual inspection for manufacturing via AI and deep learning. We also provide efficient edge AI for connected IoT edge machine learning.  

Speak with our 5G and edge computing experts to discover how our 5G IoT modules can empower you to meet the demands of the 5G era. 

Editor’s note: This blog was originally published on 8 May 2020 and has since been updated.