The explosive growth of the Internet of Things (IoT), 5G networking, and smart technology has brought about a considerable digital transformation across the globe. This has in turn, generated an accelerating demand for data storage and distribution, given the unprecedented data volumes. While sophisticated network and infrastructure are being simultaneously developed, the increase in the number of connected devices has led to data complexity.
In consequence, this has resulted in the demand for an innovation that not only helps resolve the data storage issue to some extent but also overcomes the bandwidth and latency issues that crop up while storing data in the cloud or decentralized data centers. Here’s where edge computing enters – it offers a more viable, efficient alternative as compared to the two aforementioned options.
A distributed computing framework bringing data proximity at source, edge computing is one of the latest, ingenious innovations of today. In an age where data volumes continue to expand and the requirement of IoT devices continues to increase, edge computing helps to bring computing as close as possible, to the data source. This consequently reduces latency and the usage of bandwidth. Edge computing also helps reduce the number of processes running to in the cloud and shifting them to local servers, thereby decreasing the proportion of long-distance communication between a client and server.
Literally speaking, ‘edge’ refers to the geographic location on the planet to where services are to be delivered in a distributed manner. So, as opposed to locating the data at a centralized place, edge computing helps to distribute the data computing process. In technicality, cloud computing is a faster process, however, as far as computing methodologies go, edge computing takes the cake. As mentioned earlier, it basically aims to move data computation away from the data centers and closer to the edge of the network, thereby enhancing network technology.
Statistics claim that at least 2.5 quintillion bytes of data are produced every day. With this amount, computation becomes rather difficult even for data centers. There is an increase in response time as well, in addition to diminishing bandwidth limit. With edge computing though, it is possible to have better data storage, efficient delivery of service, and an overall, enhanced digital transformation.
Given its advantages, edge computing is being used by a score of companies in daily operations, spanning industries such as healthcare, BFSI, IT, retail, energy, etc. Enlisted below are a few examples of companies adopting edge computing for faster responses and better service delivery:
· Supply chain service provider Savage recently announced that it has selected AI and edge computing leader Netradyne to use its Driveri® devices in over 1000 vehicles. Driveri for the record is an advanced fleet safety camera platform that leverages AI and vision-based edge computing to reward positive driving behavior.
· Lenovo ISG (Infrastructure Solutions Group) and VMware recently announced that the former will be the first to sell the latter’s software solution for the edge that runs on the ThinkSystem SE350 Edge Servers. The VMware software solution will be pre-loaded on security-enabled ThinkSystem SE350 along with the new solution that will be directly delivered to the customer edge sites.
· Microsoft and Verizon extended their major edge partnership recently. The extension aims to bring Verizon's 5G Edge to the Microsoft Azure Stack Edge. The combination will apparently deliver higher security levels, higher bandwidth, and increased efficiency.
· IBM and Colt Technology Services have announced plans to collaborate on edge technology solutions by helping customers adopt edge computing strategies for moving data from private data centers to the hybrid cloud framework.
· Vuzix Corporation declared recently that Verizon’s BlueJeans will be using Verizon's 5G network and deploying Mobile Edge Computing to come up with an industry-first approach that’ll help enhance service quality, reliability, and delivery and expand the performance of BlueJeans which is running on Vuzix Smart Glasses.
Speed & Latency
Quite naturally, speed comes to be one of the most distinguished advantages of edge computing. The technique allows data processing on the network edge or at a local data center, reducing latency. This enables quicker data computing, something that is vital for industries such as healthcare, defense, and BFSI.
Financial institutions, for example, use trading algorithms and the like that require fast computing. Even a fraction of delay here can prove to be disastrous. Or, consider the example of an autonomous vehicle, where data collected every second (or in multiples of seconds, more likely) matters, especially on the roadway. With edge computing, data can remain on the central server instead of traveling back and forth between the cloud.
Data comes in varied forms and holds different values; on that account, the capital spent on storing, securing, and managing all kinds of data may prove to be exorbitant. This is because, some data may be highly crucial and valued, while some may be dispensable. Edge computing eliminates this issue by enabling users to categorize data from a management perspective. With this technique, one need not spend thousands of dollars on bandwidth to connect all locations; vital data can be retained within edge locations. Edge computing helps reduce data redundancy, thereby enabling cost savings for organizations.
Given that cloud infrastructure is centralized, it proves to be quite vulnerable to cyber-attacks and other cloud security threats that can disrupt the entire operations in major organizations. Edge computing on the other hand spreads data storage across many devices and networks, thereby minimizing the impact of any attacks on the whole network.
Mobile computing has made data security even more complicated, as organizations are now more vulnerable to attacks given that enterprise data gets outside the firewall boundary. This increases the significance of edge computing, as it enables local data to remain protected within the on-premise security framework.
Edge computing considerably reduces the reliability of an individual system on the central network. Devices on the edge of a network locally store and process data, thereby improving reliability. It also ensures the use of prefabricated micro data centers that help eliminate problems arising due to poor connectivity. In case of a power outage, IoT devices can automatically handle most operations themselves.
Edge computing helps enhance scalability, as a combination of devices and local data centers can help facilitate consistent performance. However, this is not the kind of expansion that will pressurize the bandwidth of the central network. This is because you can colocation services for expanding edge networks without investing a lot of capital. One can also buy IoT devices for expanding the edge network.
The advent of digital technology has changed the dynamics of most businesses as of today. Digital transformation has come to play a crucial role in modifying business processes and customer experiences. The replacement of conventional business models with digital technologies can be credited to edge computing, to some extent. It perfectly complements important digital transformation strategies as it helps to store and manage important data required in digital use-cases. What’s more, with edge computing, manufacturers can effectively implement new digital technologies to prepare for unplanned downtime, plan maintenance, combat potential outages, and ensure via critical monitoring that machines are operating at optimum efficiency.
Implementing digital transformation involves extensive data analysis so that enterprises are able to deliver quick value to customers. As the amount of data continues to grow and more people need to connect, edge computing becomes more critical. Organizations are also combining machine learning and AI tools with large data sets, which makes it mandatory to use an edge computing approach to enhance business outcomes.
BFSI organizations have been widely adopting edge computing for digital transformation so as to bring about new consumer experiences through bots and voice-enabled assistants. Keeping devices on the network edge helps increase the consistency of services provided to users, as these services will be able to leverage wearables, connected devices, and more.
Digital transformation has found massive adoption in the retail sector. In consequence, retailers have been deploying edge computing systems in warehouses and stores. The need to have devices on the edge becomes a mandate, given the rising usage of IoT-enabled devices in e-commerce, including digital signage, point-of-sale systems, and more.
The FMCG sector also uses edge computing for digital transformation. Having devices on network edges considerably aids the adoption of digital technologies in consumer goods companies, supply chain visibility, and logistics. Using edge computing, FMCG firms can obtain visibility in operations in real-time. Edge networks also help in local data aggregation and data summarization that reduces costs on data storage and transfer.
Digital transformation has profoundly revolutionized the field of healthcare. With edge computing in the mix, it is easier for healthcare organizations to manage data locally as opposed to a centralized storage location. With devices on the edge, physicians will be able to gain instant access to vital medical data thereby enabling quicker diagnosis and spontaneous treatment.
Another profound instance proving the importance of edge computing in digital transformation is Kubernetes. Undeniably, Kubernetes is one of the best tools there is, that brings about digital transformation in enterprises worldwide. It has helped transform the way software is developed at scale. Consequently, it will continue to be deployed by organizations globally and will require edge computing to deliver optimized services to users across the healthcare, transportation, and retail sectors.
A major end-use depicting the significance of edge computing in digital transformation is remote working. It has become even more paramount in the last year since the COVID-19 pandemic took shape. The outbreak has placed a heavy burden on network infrastructure worldwide, however, with the implementation of edge computing, there has been a considerable change in the landscape. Companies have been able to use sensors and other tools to generate monitoring dashboards for real-time visibility. Automation firms have been able to consolidate resources in a centralized location and deploy edge resources to keep machines running smoothly.
The edge is already here. The concept is being used in most organizations to simplify data storage and management and provide better customer service. According to Gartner, over 50% of enterprise data is likely to be processed outside the cloud infrastructure by 2022, and possibly around 75% by 2025.
Data volumes are expected to depict an exponential growth in the years ahead. Judging by the amount of video data generated, for example, the number of edge devices is expected to cross billions soon enough. The rising number of IoT devices such as sensors is likely to increase the requirement of edge computing. The implementation of 5G-enabled IoT use cases will also need considerably more network bandwidth and computing power.
In essence, the proliferating trends of IoT, along with the need to combine cloud and edge networks will push the edge computing industry in the years ahead. IDC estimates that the edge computing market, by 2023, is likely to be valued at USD 34 billion.