Fuelled by the growing need for low-latency processing and real-time data analytics, and the proliferation of connected devices, the market for edge computing has witnessed significant growth in recent years. Edge computing helps bring computation and data storage closer to the source of data generation, thereby reducing the time and bandwidth required to transfer data, resulting in lower transmission costs. It also minimises reliance on distant data centres, reducing latency and improving data access. Additionally, it addresses security concerns associated with centralised cloud solutions by keeping sensitive data within the local environment, thus reducing the necessity to transmit data to vulnerable remote data centres. These advantages make edge computing solutions indispensable in various time-sensitive industries that cannot afford significant delays in transmitting data from the source to the centralised computing system.
Industry use cases and market uptake
Several industries are increasingly turning to edge computing to reduce long-distance communication between server and client, thereby reducing bandwidth usage and latency. In the retail space, edge computing is being deployed to enhance both the in-store as well as online shopping experience of consumers. For instance, physical stores are using edge computing solutions to run certain applications that need extremely low latency, such as a mixed reality mirrors in changing rooms, smart shelves at counters and automated checkout options. Edge computing is also being leveraged to process real-time data on consumers’ shopping behaviour from both physical stores and e-commerce platforms, thereby enhancing data analysis and customisation capabilities while mitigating concerns about cloud data aggregation risks.
Meanwhile, several manufacturing firms have started adopting edge computing solutions to store data closer to the source of generation in the production chain, thereby obviating the need to send data to a distant cloud server for analysis and response. This is speeding up analysis and correction of processes on the factory floors, and enhancing manufacturers’ predictive maintenance capabilities. In the healthcare industry, edge computing is helping deploy data, analytics and processing power where they are most needed – hospitals, operating rooms, patients’ homes. Going forward, industry experts believe that edge computing could also support advanced remote-patient monitoring by processing data from medical devices such as glucose monitors and blood pressure machines in real time, while enabling efficient management of medical equipment across hospital facilities. In the transportation sector, edge computing solutions are being devised to continuously monitor various vehicle parameters, such as temperature and mileage, and detect anomalies. The technology is also enabling connected cars to provide near-real-time and location-based weather data, helping prevent accidents in hazardous conditions.
Given these wide-reaching applications of edge computing, the uptake of the technology has increased considerably. According to industry estimates, the edge computing market is anticipated to be worth $33.9 billion by 2024 and $702.8 billion by 2033, demonstrating a compound annual growth rate of 40 per cent. Component-wise, edge computing hardware, including edge nodes, sensors, routers and endpoint devices, is projected to dominate the edge computing market, accounting for 45.1 per cent of the technology’s overall market share in 2024. Among applications, industrial internet of things is projected to capture a 28 per cent market share in 2024. Meanwhile, large enterprises are anticipated to dominate the global edge computing market in 2024 due to their wide range of resources and well-organised infrastructure.
New business opportunities for telecom companies
The rise in edge computing adoption has yielded fresh market prospects for the telecom industry, prompting telecom operators to strategically utilise this opportunity to enrich their service offerings and meet the escalating demands of consumers and businesses. By deploying edge infrastructure at their network edge, operators are able to deliver ultra-low latency services, accommodate bandwidth-intensive applications and optimise network performance to bolster user experiences. In India, major telecom operators are collaborating with equipment vendors to introduce edge solutions, facilitating the transition from centralised data management to edge computing. For instance, Bharti Airtel, operating its edge computing platform under Nxtra Digital, has partnered with IBM to deploy distributed computing platforms in large enterprises across various sectors such as manufacturing and automotive. Meanwhile, Reliance Jio Infocomm Limited (RJIL) has partnered with Cisco to introduce multi-access edge computing applications, including a content delivery network aimed at enhancing mobile video experiences through edge cloudlets, delivering lower latency and superior performance. RJIL has also integrated edge computing into its cloud-native 5G network at over 50 facilities across India. Similarly, Vodafone Idea Limited has joined forces with A5G networks to introduce mobile edge computing solutions tailored for the Indian market.
The expansion of edge computing has also generated new business avenues for tower companies. These companies are playing a pivotal role in the expansion of edge computing infrastructure by offering their extensive network of towers and infrastructure assets for the deployment of edge servers and computing resources. By partnering with tower players, organisations can accelerate the roll-out of edge computing solutions, enhance network coverage and capacity, and capitalise on emerging opportunities in the digital ecosystem.
Emerging technological trends in edge computing
- 5G integration: The rise of bandwidth-intensive applications facilitated by 5G, such as IoT, augmented reality and virtual reality, has further fuelled the need for ultra-low latency. While 5G significantly reduces latency between endpoints and towers, distant data centres still present challenges for applications requiring extremely low latency. Edge computing complements 5G by bringing computational power closer to the network edge, enhancing scalability and flexibility for applications such as smart grids and intelligent transportation systems.
- Adoption of artificial intelligence (AI) and machine learning (ML) algorithms: The integration of AI and ML with edge devices can help enable continuous offline operations, which is likely to become crucial for applications in remote or resource-constrained environments. Pre-trained models deployed at the edge can ensure intelligent decision-making without continuous cloud connectivity, benefiting areas such as agricultural monitoring and autonomous drones.
- Potential synergies with 6G: The next generation of wireless communications technology, 6G, promises unparalleled speed and connectivity, accelerating the convergence of edge computing and wireless communications. This convergence will further fuel advancements in augmented reality, holographic communications and decentralised AI applications.
- Multi-access edge computing (MEC): The use of MEC, closely linked with 5G, is also gaining significant traction. MEC enhances content delivery and user experience by bringing compute capabilities closer to end-users. While similar to edge computing, MEC is distinguished by its standard architecture, enabling mobile network operators to enhance network operations and become edge cloud providers.
- Growing deployment of micro and edge data centres: The increasing demand for edge computing is also driving the deployment of micro and edge data centres. Positioned at the network edge, these facilities bring compute and storage capabilities closer to end-users, significantly enhancing agility and efficiency in operations.
Key challenges and future opportunities
Despite its advantages, integrating edge computing into core networks introduces new cybersecurity risks. Data processed outside corporate firewalls becomes more vulnerable to attacks, compounded by physical tampering risks in uncontrolled environments. Moreover, the expanded attack surface increases the likelihood of security breaches such as distributed denial-of-service (DDoS) attacks. Enterprises also face significant challenges in managing edge environments, including the high costs associated with hardware and software modifications to support edge solutions. Upgrading network infrastructure and bandwidth to accommodate increased traffic from edge devices further adds to the financial burden. Further, integrating new edge components into existing legacy network architectures presents additional hurdles, as many of these networks were not designed with edge devices in mind, necessitating extensive modifications or new equipment acquisitions.
Notwithstanding these challenges, various industries, such as manufacturing, healthcare, transportation and retail, are recognising edge computing’s potential to drive innovation, enhance operational efficiency and improve customer experiences. The increase in the proliferation of 5G networks and the future launch of 6G services will further accelerate edge computing’s growth by supporting the development of applications that require ultra-high speed and ultra-low latency. Meanwhile, advancements in edge AI and ML capabilities will enhance real-time data analysis and predictive insights, enabling businesses to make informed decisions at the edge. With its multiple advantages, edge computing is likely to become a key component of companies’ core computing infrastructure in the next few years.
