Towards anticipate detection of complex event processing rules with probabilistic modelling
Free (open access)
Volume 11 (2016), Issue 3
275 - 283
FERNANDO TERROSO-SÁENZ, AURORA GONZÁLEZ-VIDAL & ANTONIO F. SKARMETA
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.
complex event processing, event processing rules, predictive analysis