The real value of the Internet of Things (IoT) and the Industrial Internet (I2) is ubiquitous information availability and consequently the decisions that can be made from it. The importance of ubiquitous data availability has significantly elevated attention on standards-based data sharing technologies. In this post, I’ll analyze the data sharing requirement characteristics of IoT/I2 systems and describe how the Object Management Group (OMG) Data Distribution Service (DDS) standard ideally addresses them.

Data sharing in IoT/I2
Data sharing patterns within IoT/I2 systems can be classified as follows:

Device-2-Device. This communication pattern is prevalent on edge systems where devices or traditional computing systems need to efficiently share data, such as industrial plants, vehicles, mobile devices, etc. Device-2-Device data sharing is facilitated by broker-less peer-to-peer infrastructures that simplify deployment, foster fault-tolerant, and provide performance-sensitive applications with low latency and high throughput.

Device-2-Cloud. Individual devices and subsystems interact with cloud services and applications for mediating data sharing as well as for data collection and analytics. The Device-2-Cloud communication can have wildly different needs depending on the application and the kind of data being shared. For instance, a remote surgery application has far more stringent temporal requirements than a smart city application. On the other hand, the smart city application may have more stringent requirements with respect to efficient network and energy management of the device. Thus depending on the use case, Device-2-Cloud communication has to be able to support high-throughput and low-latency data exchanges as well as operation over bandwidth constrained links. Support for intermittent connectivity and variable latency link is also quite important.

Cloud-2-Cloud. Although few systems are currently being deployed to span across multiple IaaS instances or multiple IaaS regions (such as deploying across EC2 EU and U.S. regions), it will be increasingly important to be able to easily and efficiently exchange data across cloud “domains.” In this case, the data sharing technology needs to support smart routing to ensure that the best path is always taken to distribute data, provide high throughput, and deliver low per-message overhead.

Besides the data sharing patterns identified above, there are crosscutting concerns that a data distribution technology needs to properly address, such as platform independence – for example, the ability to run on embedded, mobile, enterprise and cloud apps, and security.

The Data Distribution Service (DDS)

The DDS is an OMG standard for seamless, ubiquitous, efficient, timely, and secure data sharing – independent from the hardware and the software platform. DDS defines a wire protocol that allows for multiple vendor implementations to interoperate as well as an API that eases application porting across vendor products. The standard requires the implementation to be fully distributed and broker-less, meaning that the DDS application can communicate without any mediation, yet when useful, DDS communication can be transparently brokered.

The basic abstraction at the foundation of DDS is that of a Topic. A Topic captures the information to be shared along with the Quality of Service associated with it. This way it is possible to control the functional and non-functional properties of data sharing. DDS provides a rich set of QoS policies that control local resource usage, network utilization, traffic differentiation, and data availability for late joiners. In DDS the production of data is performed through Data Writers while the data consumption is through Data Readers. For a given Topic, Data Readers can further refine the information received through content and temporal filters. DDS is also equipped with a dynamic discovery service that allows the application to dynamically discover the information available in the system and match the relevant sources. Finally, the DDS Security standard provides an extensible framework for dealing with authentication, encryption, and access control.

Applying DDS to IoT and I2
Among the standards identified as relevant by the Industrial Internet Consortium for IoT and I2 systems, DDS is the one that stands out with respect to the breath and depth of coverage of IoT/I2 data sharing requirements. Let’s see what DDS has that make it so special.

Device-2-Device. DDS provides a very efficient and scalable platform for Device-2-Device communication. DDS implementation can be scaled down to deeply embedded devices or up to high-end multicore machines. A top-performing DDS implementation, such as PrismTech‘s intelligent data sharing platform, Vortex, which can offer latency as low as ~30 usec on Gbps Ethernet networks and point-to-point throughput of several million messages per second. DDS features a binary and efficient wire-protocol that makes it a viable solution also for Device-2-Device communication in network-constrained environments. The broker-less and peer-to-peer nature of DDS makes it an ideal choice for Device-2-Device communication. The ability to transparently broker DDS communication – especially when devices communicate through multicast – eases the integration of subsystems into IoT and I2 systems.

Device-2-Cloud. DDS supports multiple transport protocols, such as UDP/IP and TCP/IP, and when available can also take advantage of multicast. UDP/IP support is extremely useful in applications that deal with interactive, soft real-time data in situations when TCP/IP introduces either too much overhead or head-of-line blocking issues. For deployment that can’t take advantage of UDP/IP, DDS alleviates the problems introduced by TCP/IP vis-á-vis head-of-line blocking. This is done through its support for traffic differentiation and prioritization along with selective down-sampling. Independent of the transport used, DDS supports three different kinds of reliability: best effort, last value reliability, and reliability. Of these three, only the latter behaves like “TCP/IP reliability.” The others allow DDS to drop samples to ensure that stale data does not delay new data.

The efficient wire-protocol, in combination with the rich transport and reliability semantics support, make DDS an excellent choice for sharing both periodic data, such as telemetry, as well as data requiring high reliability. In addition, the built-in support for content filtering ensures that data is only sent if there are consumers that share the same interest and whose filter matches the data being produced.

Cloud-2-Cloud. The high throughput and low latency that can be delivered by DDS makes it a perfect choice for data sharing across the big pipes connecting various data centers.

In summary, DDS is the standard that ideally addresses most of the requirements of IoT/I2 systems. DDS-based platforms, such as PrismTech’s Vortex, provide device solutions for mobile, embedded, web, enterprise, and cloud applications along with cloud messaging implementations. DDS-based solutions are currently deployed today in smart cities, smart grids, smart transportation, finance, and healthcare environments.

If you want learn more about DDS check out this tutorial or the many educational slides freely available on SlideShare.

Angelo Corsaro, Ph.D., is Chief Technology Officer at PrismTech. Angelo directs the company’s technology strategy, planning, evolution, and evangelism. He also leads the strategic standardization at the Object Management Group, where he co-chairs the Data Distribution Service Special Interest Group and serves on its Architecture Board. Angelo is a widely known and cited expert in the field of real-time and distributed systems, intelligent data sharing platforms and software patterns, has authored several international standards, and has more than 10 years of experience in technology management and design of high performance mission- and business-critical distributed systems. Prior to joining PrismTech, Angelo served as a Software Scientist within the SELEX-SI Strategic and Technological Planning Directorate. He earned a Ph.D. and a M.S. in Computer Science from the Washington University in St. Louis, and a Laurea Magna cum Laude in Computer Engineering from the University of Catania, Italy.