Abstract
In the recent years, there is a massive surge in real-time data owing to the growing number of distributed software applications that continuously generates a large volume of data streams. These applications utilize new hardware technologies and data collection methods that inherently produce uncertain data. The Complex event processing (CEP) is a crucial software technology that manages highly dynamic event streams in a timely manner and determines the event patterns of interest. The CEP processes the massive data streams from different applications that depend on the reliability of data to produce accurate results. The business intelligence requires high-level of knowledge extracted from continuous streams. Ignoring uncertainty in event processing significantly degrades the performance and accuracy. Thus, efficient processing of uncertain data is vital to improving the efficiency and the accuracy of the CEP results for better decision making in business. This survey discusses the basics of uncertainty, explores models and query processing methods to deal with uncertainty. The primary contribution of this work is the survey of CEP regarding event query language and event query processing involved in identifying the complex event patterns over uncertain events. The challenges and the future directions for handling uncertain events in CEP are discussed in detail.
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