Bounding the Data-Delivery Latency of DDS Messages in Real-Time Applications

Abstract

Many modern applications need to run on massively interconnected sets of heterogeneous nodes, ranging from IoT devices to edge nodes up to the Cloud. In this scenario, communication is often implemented using the publish-subscribe paradigm. The Data Distribution Service (DDS) is a popular middleware specification adopting such a paradigm. The DDS is becoming a key enabler for massively distributed real-time applications, with popular frameworks such as ROS 2 and AUTOSAR Adaptive building on it. However, no formal modeling and analysis of the timing properties of DDS has been provided to date. This paper fills this gap by providing an abstract model for DDS systems that can be generalized to any implementation compliant with the specification. A concrete instance of the generic DDS model is provided for the case of eProsima’s FastDDS, which is eventually used to provide a real-time analysis that bounds the data-delivery latency of DDS messages. Finally, this paper reports on an evaluation based on a representative automotive application from the WATERS 2019 challenge by Bosch.