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View from the edge: The action is out on the edge

In all the excitement over IIoT, the domain of computing activity that may do most to translate IIoT technology into lasting business value has been somewhat overlooked. Yes, we’re talking about edge computing.

Of course, computing on the edge — technology infrastructure that’s located on or near production operations for data collection, data analysis and data storage — has been going on for decades. Processes like keeping an assembly line running smoothly, delivering clean water continuously and making trains run on time have long depended on edge data being gathered efficiently, with only limited connectivity to data centers. But from a computing standpoint, the edge has often been seen as something of a sleepy backwater.

All that has changed recently thanks to secular (industry-agnostic) trends that have driven dramatically more investment in computing infrastructure at the edge, followed by increased reliance on edge-gathered data for cutting-edge applications. These trends include the criticality of data to business success; the demand for real-time analysis of data in order to make better business decisions; and the increasing interconnection of “things” of all kinds in order to gather ever more and higher-quality data.

As a result, analysts estimate that 5.6 billion IoT devices owned by enterprises and governments will utilize edge computing for data collection and processing in 2020 — up from 1.6 billion in 2017. And by 2019, 40% of all IoT-collected data is expected to be stored, processed, analyzed and acted upon close to or at the edge of the network.

Real benefits, real opportunities

These trends present the opportunity to reap significant benefits for those organizations that can take advantage of them.

Consider the case of a manufacturer looking to improve decision-making and overall productivity. Most manufacturers are already operating at the edge. While their plant operations may be centralized, the data gathered by unmanned machinery or unattended workstations may be only minimally connected to their data centers and business networks. As a result, the time it takes to gather, process and analyze data on machine performance makes it difficult to identify problems, diagnose them and respond to them promptly.

With today’s edge computing infrastructure, in contrast, manufacturers can now automate the collection of large volumes of machine data (available from IoT sensors), compare it to their own historic performance or industry-wide standards, and derive usable analysis right on the shop floor. This approach drives predictive maintenance to maximize machine uptime, streamline production processes and reduce costs.

Keeping pace with the evolving edge

Meanwhile, still other business and technology trends are reshaping how computing happens at the edge and driving the need for a new edge infrastructure. Key requirements include:

  • To meet the demand for real-time analysis and support more rigorous decision-making, much more computing power at the edge is a necessity.
  • To cope with the exponential growth of data, smarter networking and data-storage processes are a must.
  • To guard against all the new intrusion points and attack vectors that are created by IIoT interconnection, highly secure connected-edge environments will be required.

IT and operations technology professionals — both of whose domains include some responsibility for computing on the edge — will have their hands full, evaluating a variety of “next-generation” technologies that are proposed as the edge infrastructure of the near future. Among these are micro-data centers, ruggedized edge servers, edge gateways and edge analytic devices. One useful screen to help triage them may be to ask: Can they — under the harshest of conditions, and often with life-or-death consequences — “self-manage”?

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