Title :
Optimizing Event Pattern Matching Using Business Process Models
Author :
Weidlich, Matthias ; Ziekow, Holger ; Gal, Asaf ; Mendling, Jan ; Weske, Mathias
Author_Institution :
Dept. of Comput., Imperial Coll. London, London, UK
Abstract :
A growing number of enterprises use complex event processing for monitoring and controlling their operations, while business process models are used to document working procedures. In this work, we propose a comprehensive method for complex event processing optimization using business process models. Our proposed method is based on the extraction of behavioral constraints that are used, in turn, to rewrite patterns for event detection, and select and transform execution plans. We offer a set of rewriting rules that is shown to be complete with respect to the all, seq, and any patterns. The effectiveness of our method is demonstrated in an experimental evaluation with a large number of processes from an insurance company. We illustrate that the proposed optimization leads to significant savings in query processing. By integrating the optimization in state-of-the-art systems for event pattern matching, we demonstrate that these savings materialize in different technical infrastructures and can be combined with existing optimization techniques.
Keywords :
business data processing; document handling; insurance data processing; pattern matching; query processing; rewriting systems; behavioral constraint extraction; business process model; complex event processing optimization; document working procedure; event detection; event pattern matching optimisation; insurance company; query processing; rewrite patterns; rewriting rules; technical infrastructures; transform execution plans; Business; Compounds; Context; Engines; Optimization; Pattern matching; Semantics; Event processing; query optimisation; query rewriting;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2014.2302306