Complex Event Processing Framework for Big Data Applications

Abstract

The fundamental requirement for modern IT systems is the ability to detect and produce timely reaction to the occurrence of real-world situations in the system environment. This applies to any of the Internet of Things (IoT) applications where number of sensors and other smart devices are deployed. These sensors and smart devices embedded in IoT networks continually produce huge amounts of data. These data streams from heterogeneous sources arrive at high rates and need to be processed in real time in order to detect more complex situations from the low-level information embedded in the data. Complex event processing (CEP) has emerged as an appropriate approach to tackle such scenarios. Complex event processing is the technology used to process one or more streams of data/events and identify patterns of interest from multiple streams of events to derive a meaningful conclusion. This chapter proposes CEP-based solution to continuously collect and analyze the data generated from multiple sources in real time. Two case studies on intrusion detection in a heterogeneous sensor network and automated healthcare monitoring of geriatric patient are also considered for experimenting and validating the proposed solutions.