Edge computing marks a transformative phase in telecommunications, driving the industry towards efficiency, reliability, and innovation.
Edge computing involves processing data closer to its origin, at the network’s edge, rather than relying on centralised cloud systems. This strategic shift significantly reduces data travel distances, slashing latency and bolstering application responsiveness.
Implementing edge computing in telecom networks offers many advantages over traditional centralised architectures.
Piyush Somani, Founder, CMD and CEO of ESDS Software Solution, emphasises the transformative potential of edge computing: “Edge computing reduces data travel distances and substantially mitigates latency by relocating data processing closer to the source. This addresses the latency challenges Internet of Things (IoT) devices encounter in telecommunications networks.”
Edge computing’s scalability and flexibility enable telecom operators to roll out new services and swiftly handle fluctuating loads.
Somani underscores the explosive growth of the global edge computing market, which is projected to reach USD 274 billion by 2025. This meteoric rise mirrors the escalating utilisation of edge computing for network optimisation, particularly in latency reduction efforts. Telecommunication giants stand poised to deliver unparalleled low-latency experiences by leveraging local data processing at the edge.
Notably, applications like online gaming, real-time video analysis, and autonomous vehicles stand to benefit immensely. The resultant swift response time elevates user satisfaction and unlocks novel use cases once deemed impractical.
Key Benefits for Telecom Networks
Implementing edge computing in telecom networks offers many advantages over traditional centralised architectures. Somani emphasises several significant benefits: “Edge computing substantially reduces latency. Critical applications can respond immediately when real-time processing takes place locally,” he points out, adding that processing data locally increases bandwidth efficiency and frees up core network resources for other uses.
He further stresses the importance of reliability, noting that “edge architectures are more reliable since edge devices can continue to operate independently during network disruptions, ensuring uninterrupted service.”
When discussing the scalability of edge computing, Somani explains that the processing capacity can be quickly adjusted at various points in the network to suit particular requirements. The scalability and flexibility that edge computing offers enable telecom operators to roll out new services and swiftly handle fluctuating loads. Besides, processing sensitive data locally according to data regulations improves privacy and security.
However, all of these involve a substantial initial setup cost.
Nevertheless, Somani points out the long-term savings in central processing and data transfer. “This makes edge computing cost-effective. It also facilitates the development of novel, latency-sensitive services that improve user engagement and innovation,” he explains.
Real-Time Data Processing for IoT Applications
Edge computing is particularly beneficial for IoT applications that demand real-time data processing, specifically for smart city initiatives and the healthcare and industrial automation sectors.
Smart Cities: Traffic management systems and public safety applications rely on real-time data to function effectively.
Edge computing reduces data travel distances, substantially addressing the latency challenges the IoT devices encounter in telecommunications networks.-
Piyush Somani, Founder, CMD & CEO, ESDS Software Solution
Healthcare: Remote monitoring and telemedicine services require immediate data analysis to provide timely medical interventions.
Industrial Automation: Manufacturing processes and supply chain management benefit from instantaneous data processing for efficient operation.
“The full potential of IoT data in telecom can be tapped through real-time processing,” says Somani, noting that the global deployment of 15 billion edge devices underscores the demand for effective data processing solutions, such as edge computing. “For example, network equipment sensor data can be used to anticipate and prevent failures before they occur or dynamically modify network resources in response to actual traffic patterns, maximising efficiency,” he says.
Experts point out that edge computing opens up new possibilities for user experiences, such as latency-sensitive services like connected automobile applications or augmented reality. It provides a local source for data processing and storage requirements for IoT. Machine learning and analytics algorithms facilitate timely decision-making, local data processing, and aggregation.
By minimising the need to send data over the network, edge data processing improves privacy and lowers vulnerability to potential cyber risks.
Overall, the edge computing industry is projected to expand at a compound annual growth rate of 34.1%, from USD 3.6 billion in 2020 to USD 15.7 billion by 2025. The demand for real-time data processing in various IoT applications fuels this increase.
Beyond IoT: Broader Applications in Telecom
Edge computing extends its benefits beyond IoT applications, offering valuable solutions for various use cases in the telecommunications sector, including Content Delivery Networks (CDNs), Augmented and Virtual Reality (AR/VR), and 5G networks.
CDN: Edge computing reduces latency and enhances the user experience by caching content closer to users.
AR/VR: Low-latency processing is essential for delivering seamless, immersive experiences.
5G: Edge computing meets the low-latency requirements of 5G applications, significantly enhancing the capabilities of next-generation mobile networks.
Enhancing Network Efficiency and Reliability
Edge computing significantly enhances the efficiency and reliability of telecom networks. By processing data locally, it conserves bandwidth and reduces operational costs. It also decreases the pressure on core networks, resulting in numerous advantages. This increases network efficiency and reduces traffic congestion, enabling faster data flow and reaction times. Moreover, the distributed nature of edge computing makes networks more resilient, ensuring high performance even in the event of individual node failures.
Data Privacy and Compliance
Deploying edge computing in telecom networks also offers substantial security benefits. Processing data at the edge reduces the need for extensive data transmission, minimising the risk of exposure to cyber threats. “By minimising the need to send sensitive data over the network, edge data processing improves data privacy and lowers vulnerability to potential cyber risks,” Somani notes.
Processing data locally also helps telecom operators adhere to data sovereignty laws and regulations, ensuring that sensitive information is managed according to local standards. “Telecom providers must ensure edge deployments comply with applicable data privacy laws. Strong data encryption is advised for every device in the network, from the edge to the core,” adds Somani.
The edge computing industry is projected to expand at a CAGR of 34.1%, from USD 3.6 billion in 2020 to USD 15.7 billion by 2025.
Edge Computing for New Services
Telecom operators can increasingly leverage edge computing to optimise network resources and deliver innovative services. By deploying edge nodes, operators can offer local content caching. This helps enhance user experience by reducing access times for frequently requested content. It also helps improve threat detection and response times, enhancing overall network security. “Since edge computing allows real-time threat detection and mitigation at the network edge, it guarantees the reinforcement of security postures,” explains Somani.
Similarly, real-time analytics provides valuable insights for better decision-making and operational efficiency. “Edge processing facilitates fast data analysis that provides insightful information for network optimisation and service enhancement,” he says, adding that the telecom operators are poised to innovate their services with edge computing.
“Operators who use this technology can set the standard for new developments in real-time data processing, network efficiency, and focused customer innovation,” Somani concludes.
