Active Complex Event Processing over Event Streams

State-of-the-art Complex Event Processing technology (CEP),while effective for pattern query execution, is limited in itscapability of reacting to opportunities and risks detected bypattern queries. Especially reactions that affect the queryresults in turn have not been addressed in the literature.We propose to tackle these unsolved problems by embed-ding active rule support within the CEP engine, hence-forth called Active CEP (ACEP). Active rules in ACEP al-low us to specify a pattern query’s dynamic condition andreal-time actions. The technical challenge is to handle in-teractions between queries and reactions to queries in thehigh-volume stream execution. We hence introduce a novelstream-oriented transactional model along with a family ofstream transaction scheduling algorithms that ensure thecorrectness of concurrent stream execution. We demonstratethe power of ACEP technology by applying it to the develop-ment of a healthcare system being deployed in UMass Med-ical School hospital. Through extensive performance exper-iments using real data streams, we show that our uniqueLow-Water-Mark stream transaction scheduler, customizedfor streaming environments, successfully achieves near-real-time system responsiveness and gives orders-of-magnitudebetter throughput than our alternative schedulers.