Complex event patterns involving Kleene closure are finding application in a variety of stream environments for tracking and monitoring purposes. In this paper, we propose a compact language, SASE+, that can be used to define a wide variety of Kleene closure patterns, analyze the expressive power of the language, and outline an automata-based implementation for efficient Kleene closure evaluation over event streams.

Pattern matching over event streams is increasingly being employed in many areas including financial services, RFIDbased inventory management, click stream analysis, and electronic health systems. While regular expression matching is well studied, pattern matching over streams presents two new challenges: Languages for pattern matching over streams are significantly richer than languages for regular expression matching. Furthermore, efficient evaluation of these pattern queries over streams requires new algorithms and optimizations: the conventional wisdom for stream query processing (i.e., using selection-join-aggregation) is inadequate.