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As a big data technology, Internet of Things (IoT) is still in the very early stages of adoption. IoT faces major challenges because, unlike many other big data technologies that can comfortably begin in a batch processing mode, the demand for IoT is almost exclusively real time. Also, the data passed between machines and then to managing staff has stringent security demands in a number of industry verticals.

Enter DDS, a Data Distribution Service that is a machine-to-machine (m2m) middleware standard that can facilitate scalable, real-time, dependable, secure, high-performance, and interoperable data exchanges. The DDS specification was developed in 2001, and later endorsed as a standard by the Object Management Group, a tech consortium. Since then, DDS has been used in government and military applications, and it is starting to be commercialized for use in other industry verticals.

What makes DDS unique is that it is 1) a messaging system that is able to transport data between humans and machines; and 2) it is also a messaging system that functions like a “moving database,” because it can carry data complete with database tables that enable users to drill into the data through data keys for real-time answers and analytics.

“You can contrast DDS with Hadoop, where you would need to serially read through every single thing,” said Stan Schneider, CEO of RTI (Real-Time Innovations), which develops and markets real-time communications platforms for IoT. “If you are an air traffic controller and there are 50,000 tracks in the air, and you only want to track the planes that are within a five mile radius of you, you can immediately screen out the data you don’t need by providing a key value that narrows down the data. From there, the DDS middleware infrastructure can find the data that you need. This is ‘moving: data.’ It fits an air traffic control scenario, because there just isn’t time to read through all of the data.”

Recently, RTI teamed with Tech Mahindra, which provides consulting, integrated engineering, connectivity, and business services in over 90 countries.

Kathikegan Natarajan, Tech Mahindra’s senior vice president and global head, talked about the how providers of big ticket items such as industrial compressors were considering a new delivery model of the service provided by the vendor, and not the equipment itself. “Customers like this concept, because they don’t have the equipment liability,” said Natarajan. “They understand that they don’t necessarily need to have such big equipment in the plant if they have an opportunity instead to just call the vendor when they need the service.” The sales arrangement would be constructed around getting the right amount of the service to the right plant at the right time, and a real-time big data communications protocol like DDS would facilitate the process.

Other IoT use case examples are:

  • A large power company that tracks the performance, quality, and condition of 900 gas powered turbines that are remotely situated in various locations;
  • A solar plant that tracks over 300 assets in 60 countries for an understanding of power conditions and influencing climate factors, such as clouds; and
  • Companies in the oil and gas industry that track the transport of goods being driven by autonomous vehicles.

As a standard messaging protocol with a real-time database mechanism, DDS has the capability to handle all of these assets, plus capture and relay information from one asset to another and to headquarters. It can scale to hundreds of thousands of integrating data points and update the data that it carries every one hundredth of a second.

“The potential of the technology is virtually limitless,” said Schneider. “Today, companies need an organizational expert to oversee a diversity of projects, and in many cases, the embedded machine space is dominated by teams of experts within a company who don’t talk to each other. This is an area that is ripe for an integrated Internet of Things.”

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DDS solves major big data IoT problems