The ever-increasing pace of digital transformation has created new data storage and computing challenges for enterprises across industry verticals. Companies are finding it difficult to process the enormous volumes of data generated on-premises and in the centralised cloud infrastructure. Moreover, with the growing use of time-sensitive data in critical decision-making processes, enterprises are looking towards solutions that require extremely low latency to smoothly transport data and provide real-time access to data. In this scenario, edge computing has emerged as a promising solution that reduces data transfer time and bandwidth usage, and lowers the cost of transmission by moving the computing power to the local infrastructure at the edge of the network rather than to distant data centres.
Edge computing places computation and data storage solutions in the environment in which they are needed and as close to the data generation source as possible. This way of working at the edge of the network reduces long-distance communication between a server and a client, thereby reducing bandwidth usage and latency. Some estimates suggest that edge computing can potentially provide improved latency and data transfer reduction to the cloud of up to 95 per cent. Besides, it addresses some of the security concerns associated with sending critical data to the cloud and brings down data transmission costs. Edge computing can also help industries make real-time decisions and scale up their operations at lower costs than traditional computing architectures.
Industry applications of edge computing
Edge computing solutions are particularly useful for time-sensitive industries that cannot afford long delays in transmitting information from the source of data generation to the centralised computing system. For instance, in the healthcare industry, edge computing solutions can be used to deploy the data, analytics and processing power where it is most needed – hospitals, operating rooms or patients’ homes. Moreover, the deployment of edge computing solutions inside ambulances can enable emergency medical teams to transmit crucial data to hospitals in real time, thereby helping hospital staff make necessary arrangements before a patient’s arrival. 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.
In the retail sector, edge computing can help significantly enhance the in-store as well as online shopping experience of consumers. In physical stores, edge computing can be used to run certain applications that need extremely low latency, such as mixed reality mirrors in changing rooms smart shelves at counters and automated checkout options. Further, edge computing can help retailers innovate on and change their applications easily given that it is more scalable than traditional on-premise or cloud solutions.
Manufacturing enterprises can also leverage edge computing to help store the data closer to the source of generation in the production chain, thereby eliminating the need to send data to a distant cloud server for analysis and response. This would help in faster analysis and correction of processes on the factory floors, thus enhancing the manufacturers’ predictive maintenance capabilities.
5G emerges as a key demand driver
The growing proliferation of 5G services has significantly increased the demand for edge computing solutions. The new bandwidth-intensive applications that 5G promises to support, such as IoT, artificial intelligence, and augmented and virtual reality, are driving the need for ultra-low latency and pushing localised data and compute resources to the network edge. Even though 5G by itself reduces the network latency between the endpoint and the mobile tower, it does not address the issue that the data centre may be distantly located and hence unable to process the information within the required time for several latency-sensitive applications.
Growing traction in the Indian market
Indian enterprises are also warming up to the idea of moving a part of their data processing to the periphery to improve network performance, decrease data traffic and reduce latency. All major telecom operators have partnered with equipment vendors to introduce their edge solutions to support this perceptible shift from centralised data management to edge computing. For instance, Bharti Airtel, which operates its edge computing platform under its data centre arm Nxtra Digital, has partnered with IBM to deploy its distributed computing platform in large enterprises across multiple industries, including manufacturing and automobile. To begin with, the two companies have entered into an agreement with passenger car manufacturer Maruti Suzuki, which intends to use Airtel’s edge computing solution to streamline its operations and increase the accuracy and efficiency of quality inspections on its factory floors.
Meanwhile, Reliance Jio Infocomm Limited has collaborated with network equipment vendor Cisco to introduce multi-access edge computing-based applications. The two companies are currently developing a content delivery network (CDN) that would significantly enhance the video experience on mobile phones. The CDN will allow operators to deliver content through edge cloudlets and provide a better user experience with lower latency and higher performance. Jio had earlier announced that it has enabled edge computing on its cloud-native 5G network at more than 50 facilities across India. Vodafone Idea Limited has also partnered with A5G networks to introduce mobile edge computing solutions for the Indian market.
Challenges and opportunities
The addition of edge computing to core networks introduces a slew of cybersecurity challenges, which the regular data centre operators may not be equipped to deal with. Security is a major concern in edge networks because data processed outside the traditional corporate firewall is more vulnerable to attacks. Since edge devices are often deployed in uncontrolled environments, they can be subject to physical tampering or damage. Further, deploying hundreds of edge computing devices creates a larger attack surface and opens the door for security breaches such as distributed denial-of-service attacks. Since edge devices are often connected to other devices and systems, they can provide attackers unauthorised access to an organisation’s network if they are not adequately secured.
Another major concern for enterprises is that the costs associated with managing and maintaining an edge environment can often become prohibitive. This is because a switch towards edge solutions entails a significant investment in modifying the existing hardware and software. Companies often need to purchase new devices such as routers, switches and servers or upgrade the existing ones to support edge computing. In addition, they may need to upgrade their network infrastructure and bandwidth to accommodate the increased traffic generated by edge devices. The software cost can also be high because businesses often need to purchase or develop new applications specifically for edge devices. These applications must be able to operate in a distributed environment, manage the data generated by edge devices and integrate with the rest of the organisation’s IT infrastructure.
Another major challenge that enterprises face when deploying edge computing is fitting the new edge components into their existing legacy network architectures. Edge devices are often deployed in remote locations, and they need to be able to communicate with the rest of the organisation’s IT infrastructure. This can be challenging because many existing network architectures have not been designed to accommodate edge devices. As a result, businesses may need to make significant changes to their network architecture or purchase new networking equipment to support an edge deployment.
For most enterprises, however, the benefits of moving to the edge far outweigh the challenges. In fact, the challenges can be effectively mitigated by taking a careful and considered approach while planning the deployment of edge solutions.
Net, net, the surge in demand for real-time processing will drive more and more businesses to add edge elements to their essential core computing infrastructure. According to industry estimates, by 2025, almost 20 per cent of the data created will have to be analysed in real time, closer to the end user, rather than sent to the core network for processing. Consequently, the global edge computing market is expected to grow at a compound annual growth rate of 38.9 per cent from $11.24 billion in 2022 to $155.9 billion by 2030.