MAD‐DDS: Memory‐efficient automatic discovery data distribution service for large‐scale distributed control network

Therampant deployment of data distribution service (DDS) as middle-ware serviceproviders for industrial network platforms has been widely investigated. AllDDS-based node discovery protocols establish communication with its intendedtarget systems by accessing matched endpoints/nodes information. These matchedendpoints/nodes information is usually embedded the system’s programmablecontrol plane which acts conveyor vehicle. The introduction ofsoftware defined networking (SDN) to characterize control from embeddeddata plane. DDS implements simple protocol (SDP) itsinherent protocol. Deploying packet exchange inserver-based collaborative distributed networked (DNC) gainedtraction. current automatic (ADP) based on SDP fraughtwith real-time limitations such high memory consumption and poor packettransmission. This work presents novel memory-efficient discoverydata (MAD-DDS) enhanced threshold bloom filters(ETBF) where ETBF stores transmission packets at simulation end-nodes. packetis further adjusted using optimized binarization decision thresholds insideADP, hence guaranteeing reduction. testbed computation recordedsignificantly improved quality (QoS) whereas numerical results depictsignificant decline in consistent transmissionrates that produces increased computational capacity.