The Internet of Things (IoT) is rapidly becoming a reality.
The combination of cutting-edge computing platforms under development in the UK and high-speed, high-bandwidth 5G and full fiber connectivity puts advanced artificial intelligence (AI)-based applications and services at the reach of almost every business in the country. We now live in a world where machines interact more than humans.
The growth of IoT depends on the expansion of the edge, as it requires a platform with excellent network connectivity, regionalized computing capacity and access to the cloud. Without these advanced capabilities, enterprises will not be able to use IoT applications at scale as they already use cloud applications. These must process the masses of data coming from the multiple sensors and devices that make up the IoT.
Shipping all data for processing to the data centers of major public cloud providers will become unsustainable due to latency and cost considerations. To mitigate this, the IoT needs gateway hubs to aggregate data, operate actuators, and translate between sensor protocols used to connect to a network. This is best suited for the edge data center where the gateway will filter out unnecessary data and pass critical information to proprietary applications hosted in the public cloud.
Industry adoption of the edge is currently dominated by the early use of MECs (Multiple Access Edge Computing Environments) providing computing services, compute, and cloud access. However, this will soon give way to metro-wide shared services. There are already real-world use cases in the smart city, transportation, and energy sectors, but wide-scale adoption will only follow when cutting-edge infrastructure platforms have fully developed their connectivity. low-latency, high-speed link to the public cloud, and local computing capabilities.
Nevertheless, at the enterprise level, three challenges typically hinder IoT adoption, starting with the need to fully understand the benefits it can bring in pure business terms. Next comes the challenge of integrating the multiplicity of IoT devices, gateways, and the data they generate into a company’s current architecture. The growth of AI applications also means that architectures will need to facilitate the transfer of more data to the edge for decision making in intelligent IoT systems.
The third challenge is the older problem of acquiring people with the required data architecture skills aligned with business process transformation. Organizations can only overcome this endemic difficulty by selecting the right partners with deep expertise in the developing relationship between edge platforms and IoT implementations.
For the IoT to accelerate, access to reliable, low-latency connectivity becomes essential. The major hardware device markets will be eclipsed by the market for applications based on continuous streams of sensor data. Applications focused on analyzing real-time and aggregated data need low-jitter, loss, and lag or dedicated high-bandwidth connectivity.
As the IoT grows, it will spread across a wide range of business applications that require different types of connectivity. Conventional Multi-Protocol Label Switching (MPLS), which has been the backbone of the Internet for a few decades, however, cannot match newer iterations of SD-WAN (Software Defined Networking in a Wide Area Network) in terms of flexibility. But MPLS will continue to underpin many services because of its reliability and scalability.
Unlike traditional WAN architectures that lack the visibility and central control required for distributed computing environments, SD-WAN brings a step change to enterprises. It makes it easy to set up multiple devices, saving time and increasing efficiency. Organizations can enforce their own policy, based on user experience, with network priority given to the most business-critical applications to avoid jitter, lag, or brownouts. Deploying new applications becomes faster and less expensive across multiple sites.
Although access to edge services is not dependent on SD-WAN, the increasing use of software to define and optimize network performance will accelerate the full operationalization of edge computing platforms and enable a chain ecosystem edge value to fully expand and programmatically interact through APIs.
The growth of edge infrastructure, which now covers around 95% of UK businesses, provides organizations with the architecture they need for IoT and AI-driven automation, efficiency and innovation .
About the Author
Simon Michie is CTO at Pulsant. Pulsant is the UK’s leading digital edge infrastructure company providing next generation cloud, colocation and connectivity services. With a network of 12 strategically located state-of-the-art data centres, Pulsant brings advances in edge computing within reach of 95% of the UK population.
Feature image: ©greenbutterfly
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