A Comparative Study of Data Sharing Standards for the Internet of Things

Although Industrial and Consumer IoT applications typically require different levels of performance, security, fault tolerance, and safety, they are both data-centric and share the same underlying architectural pattern — the Collect | Store | Analyze | Share pipeline. As a result, data sharing is a crucial architectural element that can make the difference between the success and failure of an IoT application. The challenge for industry is that there is currently a proliferation of data-sharing and messaging protocols, no set standard, and – until now – no qualitative and quantitative analysis to provide insight and direction.

Read PrismTech CTO Angelo Corsaro’s latest article in the Cutter IT Journal which aims to help IoT practitioners understand the set of data-sharing requirements they must consider and guide them in the selection of viable technologies to satisfy those requirements by registering for FREE at Cutter Consortium

Architecting Internet of Things Systems with Vortex Webcast

Date Aired: 25 February 2015
Location: Online

Why Attend:

  • Understand the key needs of Consumer and Industrial IoT systems,
  • Discover how Vortex can address the data sharing requirements of IoT systems and enable elastic analytics,
  • Learn how the different elements of Vortex support brown- and green-field deployments.


Consumer and Industrial Internet of Things (IoT) systems have to deal with massive volumes of data, collected as well as shared, with very heterogeneous targets, such as embedded systems, mobile, web and cloud applications.  Additionally, different communication patterns, such as device-to-device and device-to-cloud have to be supported to enable the right combination of fog, edge and cloud computing. Furthermore, the systems value increasingly depends on its ability to transform, in real-time, these massive amount of data into “actionable” information.

This webcast will identify the key requirements of Consumer and Industrial IoT systems and show how PrismTech’s Vortex platform is able to provide a solution that addresses them.

The webcast will last approximately one hour.

Click here to access on-demand webcast

Webcast Presenter:

Angelo Corsaro, Ph.D. is Chief Technology Officer (CTO) at PrismTech where he directs the technology strategy, planning, evolution, and evangelism. Angelo leads the strategic standardization at the Object Management Group (OMG), where he co-chairs the Data Distribution Service (DDS) Special Interest Group and serves on the Architecture Board. Angelo is a widely known and cited expert in the field of real-time and distributed systems, middleware, and software patterns, has authored several international standards and enjoys over 10+ years of experience in technology management and design of high performance mission- and business-critical distributed systems. Angelo received 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.

Building the Internet of Things with DDS

The real value of the () and the () 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 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-. 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 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 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 (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 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.

Unleashing Clinical Measurements

Medical devices are an essential element of modern medicine as they provide accurate clinical measurements such as oxygen saturation, blood pressure and temperature, x-ray and ultrasound imaging, as well as automatically administer intravenous medications, and provide support of critical life functions. In spite of the advances toward improving medical devices’ accuracy, robustness and reducing their form factor, very little has been done to pursue interoperability – most medical devices communicate their measurements through proprietary data formats and protocols thus hindering the integration with other medical systems.

This lack of seamless integration has several negative clinical implications. As an example, the use of a single clinical measurement – oxygen saturation – makes it harder than it should to detect morphine narcolepsy false positives. As the oxygen saturation measurement is very sensible to the proper positioning of the probe, several false positive can be raised in patients that are restless, perhaps due to post-operatory pain.

If multiple clinical measurements, such as breath per seconds, oxygen saturation and perhaps heartbeats, were fused together to detect morphine narcolepsy, then the number of false positives could be dramatically reduced. In addition, the actual insurgence of a narcolepsy could be detected earlier.

Ideally, medical devices should make available their measurements using a standard data model and through an open and standard protocol. The good news is that we have been working for the past year with the MDPnP (Medical Device Plug-and-Play) – a consortium of hospitals, research centers and medical device manufacturers – to explore the use of the OMG Data Distribution Service as the standard for sharing clinical data. In addition, we along with a number of the MDPnP participants have been involved with the SmartAmerica Challenge, a White House Presidential Innovation Fellows project designed to showcase Internet of Things frameworks and benefits for a variety of environments including healthcare.

DDS enables seamless, efficient and secure information sharing across any device and at any scale. As a result, once the clinical data is made available over DDS, it can be consumed virtually anywhere, on anything, and by anybody who has the proper access rights. The simple fact of making data available through DDS enables a series of use cases that are very valuable in supporting both doctors as well as patients.

Read: Applying the Data Distribution Service in an IoT Healthcare System

As an example, if we consider the image below, we see how a DDS-based platform, namely PrismTech’s Vortex, is currently being used to allow doctors to access patient data from anywhere as well as non-hospitalized patient to be continuously monitored.

Specifically, in this use case DDS makes it possible for doctors to enter a hospital room and discover the devices that are available. Doctors can then select one or more devices from which they would like to see live measurements. In case the doctors need to discuss the live data with colleagues from another hospital, the clinical data will be shipped in real-time to the remote doctors on whichever devices they have at hand–a mobile, a tablet or a notebook. In addition, data is continuously streamed to a private cloud where on-line as well as off-line analytics are executed on the various medical measurements.

Likewise, mobile personal medical devices can also make their data available seamlessly to doctors as well as to analytics applications. For instance, consider an elderly patient suffering from dyspnea. This patient can be continuously monitored while staying comfortably at home thanks to the use of a mobile oxymeter. This oxymeter would be sending data to the hospital’s private cloud via 3G/4G or WiFi where analytics applications interpret the data and respond as necessary. For example, if it’s detected that the patient needs some oxygen, a notification can go out to the patient while an alert is sent the doctor.

The beauty of DDS is that each of these use cases is seamlessly supported by its core abstraction: ubiquitous data sharing. Additionally, DDS supports for data modeling and QoS facilitates the definition of common data models for medical devices. The combination of standard data models and interoperable protocol are key elements to enable medical devices interoperability.

If you want to learn more about the DDS standard you can refer to the OMG website where you can find the specification or take a look at the educational material available on SlideShare.

Introducing Vortex the Intelligent Data Sharing Platform for Business-Critical IoT Systems

Today I’m excited to announce PrismTech’s new Vortex product, an Intelligent Data Sharing Platform for Business-Critical Internet of Things (IoT) Systems. Vortex provides efficient, secure and interoperable real-time Device to Device (D2D) and Device to Cloud information sharing. It is a key enabler for systems that have to reliably and securely deliver high volumes of real-time data with stringent end-to-end qualities-of-service (QoS).

Vortex enables system-wide data sharing for machines, devices and people. It allows users leverage the growing proliferation of data in next generation intelligent devices to create new IoT solutions. Vortex helps users to harness the ever-increasing amounts of device generated data, process the data in real-time and act on events as quickly as they occur to drive smarter decisions, enable new services / revenue streams and reduce costs. Vortex simplifies the development, the deployment and the management of large scale IoT applications, so enabling users to bring their new products and solutions to the market more quickly.

The Vortex Intelligent Data Sharing Platform consists of the Vortex Device and Vortex Cloud. The Vortex platform product bundles are designed to provide a range of capabilities that best suit the specific needs of a system:

Vortex Device enables device applications to securely share real-time data using different device platform and network configurations. This includes being able to support data sharing between devices (Device to Device) on the same Local Area Network (LAN), data sharing between devices and a Cloud-based datacenter (Device to Cloud) and between devices and a Web browser client. Vortex Device includes interoperable data sharing technologies that can support a broad range of Enterprise, Embedded and Handheld systems. Vortex Device also includes a suite of advanced tooling that helps users design, develop, test, debug, tune, monitor and manage deployed Vortex systems and systems of systems.

Vortex Cloud extends the capabilities of Vortex Device with support for data sharing over a Wide Area Network (WAN). This includes being able to share data seamlessly between applications running on different LANs via the Internet. Vortex Cloud can be used with Private, Public and Hybrid Cloud infrastructures.

To discover more please:

  • Visit the Vortex product Website
  • Register for the Vortex Introductory Webcast
  • Interact with the Vortex demo
  • Read the Whitepaper

DDS, MQTT and the Internet of Things

The commoditization of network connectivity is providing the foundation for the Internet of Things – a system in which data flows seamlessly, at Internet Scale, between network-connected devices, mobile devices, industrial and information systems.  Yet, network connectivity alone is not sufficient; another key building block needed for the Internet of Things are standards for interoperable data sharing – as without standardized open data sharing there is no Internet of Things.

The Object Management Group (OMG) Data Distribution Service for Real-Time Systems (DDS) and the upcoming OASIS Message Queuing Telemetry Transport (MQTT) provide two excellent examples of standards that address the Internet of Things.

Introduced in 2006, DDS has established itself as the standard for peer-to-peer real-time data sharing in Operational Systems , such as Air Traffic Management Systems, Medical Systems, and Combat Systems.  DDS has recently experienced rapid adoption as the foundation for an increasing number of Intelligent Systems in applications such as Smart Cities, Smart Grids, and m-Health.

MQTT was introduced in 1999 by IBM as a publish / subscribe, extremely simple and lightweight messaging protocol, designed for constrained devices and low-bandwidth, high-latency or unreliable networks.

DDS and MQTT share some common principles, such as parsimony and efficiency, temporal decoupling and anonymity, yet each technology has some unique features that make it most applicable for certain use cases.

For instance, MQTT is most suitable for sporadic messages and highly resource constrained devices whilst DDS is most suitable for those applications that require real-time data exchange – meaning applications in which data has an inherent temporal validity and in which stale data should never delay fresh data– and tight control over the Quality of Service (QoS).  In addition DDS supports peer-to-peer (infrastructure-less) communication, a feature that comes in handy for device-to-device communications.

In summary, DDS and MQTT are two very good standards for data sharing in the Internet of Things. DDS provides support for both Device-to-Cloud (Device-to-Data Center) communication as well as Device-to-Device.  MQTT provides very good support for Device-to-Data Center communication.

Finally, I have produced an ondemand webcast on Building the Internet of Things which you can access at: http://www.prismtech.com/opensplice/resources/webcast-archive.