Seeking Higher Performance in Real-Time Data Processing through Complex Event Processing

  1. Ortiz, Guadalupe 1
  2. Bazan-Muñoz, Adrián 1
  3. Caballero-Torres, Pablo 1
  4. Rosa-Bilbao, Jesús 1
  5. Medina-Bulo, Inmaculada 1
  6. Boubeta-Puig, Juan 1
  7. García-de-Prado, Alfonso 2
  1. 1 Department of Computer Science and Engineering UCASE Software Engineering Group, University of Cadiz, Spain
  2. 2 Computer Architecture and Technology Department UCASE Software Engineering Group, University of Cadiz, Spain
Actas:
ALLDATA 2023: The Ninth International Conference on Big Data, Small Data, Linked Data and Open Data

ISSN: 2519-8386

ISBN: 978-1-68558-041-4

Año de publicación: 2023

Páginas: 29-34

Tipo: Aportación congreso

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Resumen

Today, data processing has become a key functionality of multiple diverse applications. Large amounts of data from disparate sources must be processed in streaming in order to have real-time knowledge of the domain in question and thus be able to make the most appropriate decisions at each instant of time. This streaming processing has been successfully achieved by introducing Complex Event Processing (CEP) techniques into the solutions provided. Although these solutions have proven their effectiveness in various software architectures and application domains, there is still a need for further research on how to achieve better performance depending on the needs of the application. This paper attempts to shed some light in this area by comparing various configurations of a CEP engine, aiming for better performance in real-time data processing.