Event Broker Marshalling for Publish-Subscribe Systems

The system performs preliminary filtering and marshalling of events based on subscription parameters before delivering events to subscribers. The event broker pre-processes events by matching them against subscription criteria, so that only relevant events are forwarded to each subscriber. This preliminary action prevents unnecessary processing and resource consumption while ensuring complete delivery of all relevant events.

The event broker applies different filtering and marshalling operations tailored to each subscriber's specific subscription parameters. Instead of a uniform filtering approach, the system customizes event processing for each subscriber based on their individual needs, topics of interest, and event receive rate preferences. This local quality approach ensures high event availability for relevant events while maximizing processing efficiency by avoiding unnecessary events for each subscriber.

The event broker extracts and delivers only the specific events that match subscriber subscriptions to machine learning models. By filtering out unrelated events before they reach the ML models, the system ensures that models receive complete information about relevant events (maintaining inference accuracy) while dramatically reducing the volume of events that require computational processing (reducing computational overhead).