Real-Time Innovations

The Internet of Things (IoT) paradigm has given rise to a new class of applications wherein complex data analytics must be performed in real-time on large volumes of fast-moving, heterogeneous sensor-generated data. Such data streams are often unbounded and must be processed in a distributed and parallel manner to ensure timely processing and delivery to interested subscribers.

The OMG Data Distribution Service (DDS) has been deployed in many mission-critical systems and increasingly in Internet of Things (IoT) applications since it supports a loosely-coupled, data-centric publish/subscribe paradigm with a rich set of quality-of-service (QoS) policies. Effective data communication between publishers and subscribers requires dynamic and reliable discovery of publisher/subscriber endpoints in the system, which DDS currently supports via a standardized approach called the Simple Discovery Protocol (SDP).

Event-driven design is fundamental to developing resilient, responsive, and scalable reactive systems as it supports asynchrony and loose coupling. The OMG Data Distribution Service (DDS) is a proven event-driven technology for building data-centric reactive systems because it provides the primitives for decoupling system components with respect to time, space, quality-of-service, and behavior. DDS, by design, supports distribution scalability. However, with increasing core count in CPUs, building multicore-scalable reactive systems remains a challenge.

This whitepaper describes a powerful C++ template library to allow users to describe their types in plain C++ and use those types directly for data-centric communication over DDS. The library transforms native C++ types into equivalent run-time TypeObject representation as specified in the DDS-XTypes standard. The library obviates the need to describe application-level data-types in external representations, such as IDL, XSD, XML, and DynamicData.