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In the last decade, the detection and processing of complex events has increasingly gained importance, since it allows an immediate reaction to changes to instantly adapt business processes to varying situations. However, currently there is a discrepancy in tools available for modelling constraints on business processes, mainly rule-based systems, and those providing complex event processing. This paper deals with the challenge of identifying unneeded events in rule-based systems in order to delete them to save memory to enable event processing. We adapt an existing approach of lifetime calculation to suit interval-based semantics for event timestamps. In a subsequent validation of our concepts, we were able to demonstrate that they lead to improved event processing capabilities compared to a traditional rule-based system.

EVENT LIFETIME CALCULATION BASED ON TEMPORAL RELATIONSHIPS