Content-based Filtering Discovery Protocol (CFDP): Scalable and Efficient OMG DDS Discovery Protocol

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). For large-scale systems, however, SDP scales poorly since the discovery completion time grows as the number of applications and endpoints increases. In order to scale to much larger IoT applications, a more efficient protocol is required.

This paper makes three contributions to overcoming the current limitations with DDS SDP. First, it describes the Content-based Filtering Discovery Protocol (CFDP), which is our new endpoint discovery mechanism that employs content-based filters to conserve computing, memory and network resources used in the DDS discovery process. Second, it describes the design of a CFDP prototype implemented using RTI Connext DDS. Third, it analyzes the results of empirical studies conducted in a testbed we developed to evaluate the performance and resource usage of our CFDP approach compared with SDP.