Data Management For IIoT Devices: Is Your Software Stack Up To Task?

There’s a major shift underway in how edge devices handle data processing and storage.

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By now we’ve heard about the great things the IIoT will bring; increased productivity, improved operational efficiency, innovation, greater competitiveness the global markets, and so on.

But there’s a major shift underway that’s worth mentioning.

…what is this shift?

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Image courtesy of EETimes.

The rise of the edge device
Today we are seeing intelligent processing and data analytics being pushed out of the cloud and down toward the edge of a network. What was once solely a cloud-based system where decisions were made up in the cloud, has evolved to what some are calling FOG computing – moving data collection and processing away from the cloud and closer to the ground where to the devices themselves perform and interact. (This is not to say cloud computing is going away, the two actually complement one another.)

When it comes to the IIoT, data is now not only being stored and managed in controllers and gateways, but also in sensors and the devices themselves, capturing data and responding to real-time events as they happen.

With so much data at the device level, reliable data storage and management are essential to a well-oiled IIoT network. Edge devices today need massive and reliable storage capabilities so that data analysis, event logging, alarm signaling, and diagnostic communication can happen in real time (without involvement from the cloud, or humans for that matter) on the device with outcomes quickly transmitted across the network.

IoT/IIoT is driving up data exponentially
According to CD Net production of data on edge devices connected to the IIoT is expected to exceed 500 zettabytes per year by 2020. Already in 2016, we have some impressive examples:

ge-jet-engine

  • A jet engine can generate as much as 10 GB of data per second. The data is useful in achieving optimal fuel efficiency as well as performing other diagnostic and performance-related events.

GE is actively involved in the IIoT. Image: GE

  • A single residential smart meter on the power grid is capable of managing upwards of 20 MB of data per hour. This type of data is used to optimize efficiency and reduce the environmental impact of energy production.
  • A modern-day F1 race car can generate 90 GB of data per race. The data not only helps the driver and team win the race, but serves as valuable data protecting driver and crew.

The bottom line: more and more data – critical data – is residing on the end device.

Efficient database management
Database management systems were created a very long time ago, and they are still with us today. But the difference today is that compute processing back in the 1960’s is nothing compared to what an embedded processor can do in 2016.

Recognizing the importance of database management at the device level, Mentor Graphics has partnered with two leading software providers. Working with Mentor and our Mentor Embedded Linux, this partnership has created an invaluable approach to data management at the device level.

Of course, serving at the foundation of this partnership is Mentor Embedded Linux, the preferred choice among modern developers because it offers a rich tapestry of parts and pieces. (If one where to look outside of Mentor Embedded Linux, there are risks involved in compatibility and buggy software, which can derail product delivery.) Mentor Linux is a pre-tested, commercially supported, and customizable platform perfectly suited for IIoT devices and allows team to quickly and easily scale to productivity.

The partners involved in working with Mentor Embedded Linux include:

datalightDatalight, Inc.

Datalight has been developing software to protect vulnerable data in embedded devices for close to 30 years. It is active in industries such as industrial controls, automotive, smart energy, and aerospace. The company allows devices and embedded systems to run more reliably, responsively, and in a more cost-effective manner. Mentor used Datalight’s Reliance Nitro file system as a key ingredient in this partner solution.

raima-logoRaima, Inc.

An integral part to this reliable data storage solution is Raima Database Manager (RDM). When combined with Datalight Reliance Nitro file system, a device is able to save its data securely and atomically while minimizing the frequency and size of Flash device writes.

Mentor Graphics, Raima, and Daylight successfully collaborated to deliver a secure, reliable, and optimized data storage configuration for IIoT devices. Details on this collaboration can be seen in this joint webinar.

The team has also produced this short white paper.

Conclusion
Using database-driven data at the edge helps things move faster and reduces network traffic by controlling the data that needs to be transmitted. Having this kind of performance also improves decision time and responsiveness.

But none of this could be possible, or at least not fully realized, if data stored on the device is not reliable or is not organized at optimal levels. The goal is to have your storage media outlast your device.

Having secure and reliable data stored at the device level is yet another way we can build the IIoT of today and tomorrow. And build an IIoT that delivers on all of its wonderful promises.



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