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.