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How the network edge will shape IoT applications

2020-03-30 11:43:24
The network edge is where the action is, with its ability to move processing power for data analysis as close to the user as possible, reducing network latency to absolute minimums. A new webinar looks at how the edge is changing and its importance to IoT applications such as autonomous drones, collaborative industrial robots, and smart video analytics.

Importance of the edge
IoT application workloads today reside in three general locations:
The network core, encompassing public cloud and hosting as well as large-scale enterprise data centers;
The “near-edge,” which includes micro-data centers closer to the end point as well as the emerging public network edge computing infrastructure;
And the edge, which can exist on the device or machine itself or on servers or gateways that are physically adjacent.
Increasingly, the edge and near-edge are merging, 451 Research says, with powerful edge servers and gateways providing terabytes of storage and large amounts of computing power. The near-edge infrastructure is rapidly becoming indistinguishable from the edge itself.
When it comes to IoT, it is at the edge and near-edge where the majority of IoT processing is being done, and that percentage is only likely to rise as enterprises reassess how their workloads can be most effectively handled.

Getting it done
How is all this going to get done? It will require enterprises to take advantage of the best developer-driven companies when it comes to the IoT applications they designate and the data analysis they need to take full advantage of those applications.
Being able to deploy servers quickly and tie them through the dedicated IoT network – specifically the IoT platform – will allow enterprises to make their IoT operations as flexible as possible.
All of these elements come together in the IoT edge, which is clearly becoming the new frontier of computing, processing, and data analysis.
As 451 Research points out, the type of processing that occurs at the IoT edge depends on several factors, among them:
The type of data analysis that needs to be undertaken
How quickly the results of that analysis are required
How much data is generated in total, and how much of that might yield valuable insight
Whether the data is likely to be analyzed on its own or integrated with data from other sources
But the top task located at the IoT edge is data analysis, and increasingly that means analysis enhanced by the use of artificial intelligence and machine learning.

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