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Edge Computing Middleware: How It Can Tame IoT Complexity
SAS is also working with GE Transportation, which recently merged with Wabtec, to provide analytics on locomotives in North America to help cut down on fuel usage. As the locomotives move along tracks at the network edge, they rely in part on SAS Event Stream Processing.
In the locomotive example, Wabtec provides EdgeLINC software to support edge analytics, and has embedded the SAS analytics. EdgeLINC also incorporates “a lot” of open source technology, said Garret Fitzgerald, general manager of transport intelligence at GE Transportation.
“We have the ability to support all our customers who have a mix of internal technology and open standards,” he said. The EdgeLINC API also allows customization that’s usually needed in the transportation industry.
Advice to IT: Get the Big Picture First
To gain edge analytics insight, companies need to have a holistic view of how edge computing will fit into an overall architecture, IDC’s Nadkami argued. “One of my pet peeves with AI is that it’s a software approach, which dictates having the right hardware,” he said. “Doing analytics is a function of knowing the overall [goal] and the time-to-value” for an investment.
How a company picks edge middleware is “not only a decision on hardware and software,” he added. “You have to look at edge end-to-end and implement a strategy.”
In fact, some edge computing trials and rollouts haven’t worked out, even when companies have invested heavily. “It’s trial and error and if anybody has been able to pull it off without trial and error, that’s a miracle,” Nadkami added. “Edge is so nascent that nobody pulls it off without some iterative process.”
