Bloom filter-based discovery protocol for DDS middleware

The Data Distribution Service (DDS) middleware has recently been standardized by the OMG. Prior to data communication, a discovery protocol had to locate and obtain remote DDS entities and their attributes. Specifically, DDS discovery matches the DataWriters (DWs) and DataReaders (DRs) entities (Endpoints) situated in different network nodes. DDS specification does not specify how this discovery is translated “into the wire”. To provide interoperability and transparency between different DDS implementations, the OMG has standardized the DDS Interoperability Wire Protocol (DDS-RTPS). Any compliant DDS-RTPS implementation must support at least the SDP (Simple Discovery Protocol). The SDP works in relatively small or medium networks but it may not scale as the number of DDS Endpoints increases. This paper addresses the design and evaluation of an SDP alternative–which uses Bloom Filters (BF)–that increases DDS scalability. BFs use Hash functions for space-efficient probabilistic data set representation. We provide both analytical and experimental studies. Results show that our approach can improve the discovery process (in terms of network load and node resource consumption), especially in those scenarios with large Endpoint per Participant ratios.

► The DDS-RTPS standard specifies the SDP discovery protocol which lacks of scalability.
► Bloom filters have been applied to improve SDP, hereafter referred to as SDPBloom.
► Bloom filter usage suppresses most of the unnecessary discovery traffic.
► Benefits mainly depend on the matching degree between entities in the network.
► SDPBloom can reduce network load and node resources consumption.