A Review on Complex Event Processing Systems for Big Data

Abstract

Over the years, huge volumes of data are continuously generated due to the increasing number of applications, efficient methods are therefore required to determine the event patterns of interest and manage highly dynamic events in real-time. There has been increasing demand for active systems within Internet of Things, which can automatically react to events that come from various sources. Complex Event Processing (CEP) is an impressive technology that can deal with large amount of data from various sources depending on the consistency of data to generate exact result to process dynamic data in real-time. Thus, understanding existing CEP methods and tools is essential to develop a robust and effective CEP system. In this paper, we had briefly described about event processing, CEP with different engines and CEP for uncertainty. This paper reviewed CEP tools available in the market from 2010 to 2017. It has been found that there are many commercialized and open-source CEP tools in current market, where commercialized tools are used for business intelligence purpose and open-source tools are mostly used for academic purposes. Most of the available processing tools are Query-based and very few are working with Machine learning. There is a huge potential for further research in the use of Machine Learning in Complex Event Processing.