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A distributed complex event processing (CEP) system based on the Esper engine

Kyriakopoulos Konstantinos

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URI: http://purl.tuc.gr/dl/dias/A9607779-0C1F-4B89-AEF0-472B93D7A3E7
Year 2018
Type of Item Diploma Work
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Bibliographic Citation Konstantinos Kyriakopoulos, "A distributed complex event processing(CEP) system based on the Esper engine", Diploma Work, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2018 https://doi.org/10.26233/heallink.tuc.78849
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Summary

The evolution of Big Data in the recent years has been posing continuous challenges to the Data Science field. More specifically, the multiple sources of information along with the continuous growth and fast transmission of data have raised the need for real-time data analysis. In order to fill this need complex event processing has emerged. Complex event processing is a technique used for analyzing multiple streams of data in a pattern-based manner. The concept behind complex event processing is the establishment of relationships between events of information and the correlation of the events for specific patterns. Events may derive from multiple streams so CEP fulfills the need for distributed event detection. In this thesis, a distributed complex event processing (CEP) system based on the Esper engine is implemented. Esper is an open-source software suitable for complex event processing and real time data analysis. The Esper engine lies on top of the Ferari project which serves as a framework for distributed streaming processing and utilizes the functionalities of various platforms such as the Apache Storm. The goal of this work is to integrate the Esper engine into the Ferari project and conduct experiments while taking advantage of Ferari's services and components. These experiments demonstrate Esper's capabilities and its efficiency as a CEP engine

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