The spectrum of distributed real-time applications is broad, spanning military systems, financial trading, telecommunications, factory automation, traffic control, and medical imaging. While these systems are networked, today they are not really well connected; there is little control, or even understanding, of critical issues such as delivery timing, bandwidth utilization, or fault handling. As a result, most systems share only a fraction of the information required to develop a truly distributed application.

Recent advances in real-time middleware technology offer the possibility of getting the right data — making possible a switch from code-centric or architecture-centric thinking to data-centric design. Recently, the Object Management Group’s (OMG) Data Distribution Service for Real-Time Systems standard (DDS) codified the data-centric approach. DDS specifies a rich API for publish-subscribe data delivery. More critically, DDS is the first standard that specifies flexible Quality of Service (QoS) parameters that control real-time delivery. This paper examines the challenges faced by distributed real-time systems and dives into the depths of the DDS standard, revealing how data-centric design can be implemented within real-time constraints.