Edge computing powers many of the worlds' latest innovations, such as the Internet of Things (IoT), autonomous vehicles, remote surgeries, and augmented reality (AR). As these technologies require essential capabilities to process and analyse vast quantities of data in real-time to produce actionable insights, edge computing can drive powerful transformations in how businesses utilise data and drive effective processes for decision-making.
With the increasing need for infrastructure to support an expanding connected devices ecosystem, as well as the acceleration of digital transformation initiatives within the Asia Pacific (APAC) region, analysts predict that edge computing in APAC will reach US$5.8 billion by 2024, representing a compound annual growth rate of 21% over five years. By then, APAC will become the second-largest edge computing market after North America.
In Singapore, the government is looking to integrate various automation capabilities across the city-state – including automated vehicles, drones, assistive robots and sensors – as part of its Smart Nation initiative. All these applications require the processing of highly time-sensitive data on the device itself or near the source of data, making edge computing an essential element to ensure the success of Singapore's digitalisation efforts.
According to Minister for Trade and Industry Gan Kim Yong, the roll-out of 5G network which is expected to propel edge computing growth in Singapore, is on track to meet Singapore’s target of deploying 5G standalone outdoor coverage across half of Singapore by end-2022, and nationwide by end of 2025. The 5G network's speed, which is 10 times faster than that of the 4G, opens possibilities for far-away sensors to give real-time updates from connected devices and enhance the distributed computing capacities of edge.
Undoubtedly, edge computing opens up capabilities to support more sophisticated applications, especially those that need to overcome latency and bandwidth limitations. However, IT leaders should not be influenced by the hype surrounding edge computing. Instead, the decision should be based on the practical application of technology, and how it can help achieve the objectives of the business.
Edge computing and increasing need for faster, more efficient data transfer
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Latency is increasingly becoming an issue as information moves through data centres, typically hosted in the cloud. With edge architectures, compute and storage systems reside as close as possible to the components, devices, applications and humans that produce and use the data.
This proximity removes processing latency by reducing the distance that data must travel and thus makes data processing faster and more reliable.
Data no longer has to be sent from the edge of the network to a central processing system, and then back to the edge. By eliminating the distance between data sources and devices, edge computing brings technologies close to wherever they need to run.
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With the distributed data processing capabilities of edge computing, latency problems can be addressed, networks can operate faster, which enables time-critical applications to react to data.
Moreover, with edge computing, transferring data becomes faster and less expensive by sending smaller file sizes, decreasing the need for larger server resources, which can help organisations to be more cost-efficient.
Defining what edge computing means for the business
The first step organisations must take when deciding whether to integrate edge computing into their overall technology strategy is to identify their data types. Questions such as "How critical is this data to the business?" "Which data requires real-time updates?" and "How much space does data take up?" need to be defined.
Cloud computing offers vast resources and centralised servers stored in data centres while edge computing brings key processes to the edge of the network for faster and optimised asset performance. Organisations must understand the computing requirements of the business by reflecting on their need for connectivity, data migration and bandwidth requirements, as well as their latency threshold.
Deploying edge computing also needs an assessment of the business' data storage requirement. The level and location of the data storage require particular attention, especially if the asset needs to be regularly accessed. Business and IT leaders also must consider whether processing data closer to the point where it is generated would offer new functionality for the business or the customers.
With the growing number of cyber-attacks, security is another key consideration when rolling edge computing plans for the business. While a well-designed edge computing solution is as secure as any other system, particular attention must be paid to the increase in exploitable attack vectors associated with a proliferation of edge devices. Most security issues specific to edge computing relate to poorly implemented and maintained codes on edge devices.
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Moving forward with edge computing
As data volumes are growing, more companies in the Asia Pacific are beginning to think harder about where to put data for optimal costs and performance. The importance of a comprehensive data strategy continues to grow as the Internet of Things (IoT) revolution forges ahead and more devices are brought online, fuelling an explosion in data processing and storage requirements.
As businesses start looking for solutions that answer their data processing needs, edge computing is poised to make a big impact on how organisations collect, analyse, synthesise and use their data beyond the confines of their data centre and enterprise networks.
Sandeep Bhargava is the managing director of Asia Pacific Japan (APJ) at Rackspace Technology
Photo: Unsplash
