Pattern rewriting framework for event processing optimization

A growing segment of event-based applications require both strict performance goals and support in the processing of complex event patterns. Event processing patterns have multiple complexity dimensions: the semantics of the language constructs (e.g., sequence) and the variety of semantic interpretations for each pattern (controlled by policies). We introduce in this paper a novel approach for pattern rewriting that aims at efficiently processing patterns which comprise all levels of complexity. We present a formal model for pattern rewriting and demonstrate its usage in a comprehensive set of rewriting techniques for comple pattern types, taking various semantic interpretations into account. A cost model is presented, balancing processing latency and event throughput according to user's preference. Pattern cost is then estimated using simulation-based techniques. This work advances the state-of-the-art by analyzing complex event processing logic and by using explicit means to optimize elements that were considered "black box." Our empirical study yields encouraging results, with improvement gain of up to tenfold relative to the non optimized solutions that are used in the current state-of-the-art systems.