Complex event processing with T-REX

Several application domains involve detecting complex situations and reacting to them. This asks for a Complex Event Processing (CEP) middleware specifically designed to timely process large amounts of event notifications as they flow from the peripheral to the center of the system, to identify the composite events relevant for the application. To answer this need we designed T-Rex, a new CEP middleware that combines expressiveness and efficiency. On the one hand, it adopts a language (TESLA) explicitly conceived to easily and naturally describe composite events. On the other hand, it provides an efficient event detection algorithm based on automata to interpret TESLA rules. Our evaluation shows that the T-Rex engine can process a large number of complex rules with a reduced overhead, even in the presence of challenging workloads.

► We introduce TESLA, a new language for Complex Event Processing.
► We show how TESLA rules can be translated into automata for efficient processing.
► We introduce T-Rex, an efficient Complex Event Processing engine explicitly designed to process TESLA rules.
► We evaluate T-Rex, showing its advantages, even when compared to a mature commercial product.