Towards Anticipate Detection of Complex Event Processing Rules with Probabilistic Modelling

Towards Anticipate Detection of Complex Event Processing Rules with Probabilistic Modelling

Fernando Terroso-Sáenz Aurora González-Vidal Antonio F. Skarmeta 

Department of Information and Communications Engineering, Computer Science Faculty, University of Murcia, Spain

Page: 
275-283
|
DOI: 
https://doi.org/10.2495/DNE-V11-N3-275-283
Received: 
N/A
| |
Accepted: 
N/A
| | Citation

OPEN ACCESS

Abstract: 

Nowadays, Big Data implies not only the need of processing high volume of data, but also do it in a timely manner. In this scope, the Complex Event Processing (CEP) paradigm has arisen as a prominent real-time rule-based solution. Due to its reactive nature, a CEP system might suffer from slight delays in the activation of its rules that could not be desirable in certain environments. As a result, the present work introduces a novel mechanism that intends to anticipate the activation of event-based rules and, thus, come up with even faster CEP systems. This is achieved by means of a probabilistic modelling of each rule’s precondition. Finally, the proposal includes a preliminary evaluation so as to show its suitability.

Keywords: 

 complex event processing, event processing rules, predictive analysis.

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