Edge computing – defined as computing infrastructure that exists close to the source of data – performs hosting, storage, computing and analysis and pushes aggregate data to a centralised plant for use in a meaningful way. This article by Dave Laurello CEO of Stratus Technologies, a Rockwell Automation Encompass Partner, takes a closer look at factors that are pulling edge computing into the mainstream.

Consolidation and the centralised nature of cloud computing has proven cost-effective and flexible, but the rise of the IIoT and mobile computing has put a strain on networking bandwidth. Ultimately, not all smart devices need to use cloud computing to operate. In some cases, architects can – and should – avoid the back and forth. Edge computing could prove more efficient in some areas where cloud computing operates.

Edge computing the next wave of data centre modernisation

Analysts estimate that by 2020 more than 5.6 billion IoT devices owned and operated in enterprise and government environments will utilise edge computing for data collection. This represents significant growth over 1.6 billion devices in 2017 [1].

The reason edge computing is emerging as the better alternative in IoT environments is that while most information will be uploaded and processed via the cloud, some business-critical applications will demand real-time data. This requires the use of a physical or virtual computing infrastructure on the edge of the network to minimise the bandwidth needed to access data that is centrally stored.

What is edge computing?

Just as IoT is becoming more mainstream, more industries are using the technology to leverage real-time data to drive better decisions. The impact of IoT is well documented in industries such as retail and healthcare. But today what was once an emerging technology is now helping to revolutionise industries in need of innovation, such as manufacturing, transportation, energy, food and beverage, and waste management.

Edge computing permits data processing closer to where it's created (i.e., motors, pumps, generators or other sensors), reducing the need to transfer that data back and forth between the cloud. As an example, many manufacturing companies are collecting data on the shop floor via IoT sensors and analysing it to drive predictive maintenance and optimise machine performance.

Every IoT device collects data for processing and analysis. Edge computing can process the data instantly and arm manufacturers with the information to make faster, more informed decisions that optimise the supply chain, streamline production, and reduce costs.

There’s no distinct hardware definition of industrial edge computing; it’s in the eye of the beholder as to how much compute power or data response may be required in a given application or across a specific production process. Dedicated servers with virtualisation can host apps with significant footprints, store related production data, communicate to the cloud, and perform on-board analytics in the footprint of an appliance, server or PC in a PLC rack.

Industrial firms must agree internally on standards of functionality required for various processes and then on the appropriate hardware and vendor(s) to fulfill the need. When referring to edge, it will almost always be on-premise or at-asset to avoid over-generalising the IT infrastructure at the plant level.

Depending on organisational viewpoint, edge infrastructure can be complementary to or inclusive of level 1 or 2 control and information layers of the production process. An organisation can define industrial edge as an extension of cloud activities or as an extension of control activities based on requirements of speed, data structure, volume and velocity. Organisational agreement on location, such as an unmanned pumping station, capabilities, use cases and desired outcomes is critical before conducting any pilots or scalable implementations.

Improved security and compliance

IT teams are sensitive to the risks involved whenever data is transferred between devices and the cloud. Edge computing alleviates the risk in some environments by making much of that data transfer avoidable. With edge computing it is possible to filter sensitive information locally and only transfer data important to model-building information to the cloud. This means enterprises can build an adequate security and compliance framework that meets their needs and ensures compliance with audits.

Closing modernisation gaps

IoT and edge computing are driving the next wave of data centre modernisation and improvement. Virtualisation represents an affordable means of updating and innovating IT environments and addressing immediate needs with cutting-edge technology without breaking the bank. What’s more, edge computing enables enterprises to capitalise on modern devices without sacrificing existing legacy systems. This is because edge computing devices can be used as a communication bridge between legacy systems and modern machines.

This allows legacy industrial environments to connect to modern devices or IoT solutions and provide immediate benefits of capturing and integrating real-time data from both legacy systems and modern devices for better decisions.

Capitalising on the edge opportunity

In order for any organisation to reap the maximum benefits that edge computing can deliver, a new technology approach and computing infrastructure are needed. New innovations, such as the Stratus ztC Edge, provide built-in virtualisation, automated protection, and managed services – all to provide versatile computing platforms for running business critical applications.

Edge is still in early stage adoption, but one thing is clear: Edge devices are subject to largescale investments from cloud suppliers to offload bandwidth and latency issues caused by an explosion of Internet of Things (IoT) data in both industrial and commercial applications. Edge soon will likely increase in adoption where users have questions about how or if the cloud applies for the specific use case. Cloud-level interfaces and apps will migrate to the edge. Industrial application hosting and analytics will become common at the edge, using virtual servers and simplified operational technology-friendly hardware and software.

Benefits in network simplification, security and bandwidth accompany the IT simplification. Establishing an operational architecture with the strategic flexibility to use distributed computing and virtualised servers creates a production environment to optimise people, process and technology in a scalable manner, without the need to lock into a specific vendor or solution construct.

However, as many operations will rely on legacy systems to fi t into an overall architecture, virtualised hosts, data management and open API tools will be needed for a future-proof production environment.


[1] Tech Insider, BI Intelligence, “Edge Computing in the IoT: Forecasts, Key Benefits, and Top Industries Adopting an Analytics Model that Improves Processing and Cut Costs,” October 2016.

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