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Processing event streams is an increasingly important area for modern businesses aiming to detect and efficiently react to critical situations in near real-time. The need to govern the behaviour of systems where such streams exist has led to the development of numerous Complex Event Processing (CEP) engines, capable of detecting patterns and analyzing event streams. Although current CEP systems provide real-time analysis foundations for a variety of applications, several challenges arise due to languages’ limitations and imprecise semantics, as well as the lack of power to handle big data requirements. In this paper, we discuss such systems, analyzing some of the most sensitive issues in this domain. Further, in this context, we present our contributions expressed in LEAD, a formal specification for processing complex events. LEAD provides an algebra that consists of a set of operators for constructing complex events (patterns), temporally restricting the construction process and choosing among several selection and consumption policies. We show how to build LEAD rules to demonstrate the expressive power of our approach. Furthermore, we introduce a novel approach of interpreting these rules into a logical execution plan, built with temporal prioritized coloured petri nets.
The paper will be published at the 13Th ACM international Conference on distributed and event-based systems taking place in Germany. In the meantime, do not hesitate to contact our R&D department at firstname.lastname@example.org to discuss how you can leverage neural topic models in your projects.
Anas Al Bassit, Skhiri Sabri, LEAD: A Formal Specification For Event Processing, in 13Th ACM international Conference on distributed and event-based systems 2019