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Graphcep : Real-time data analytics using parallel complex event and graph processing

Title data

Mayer, Ruben ; Mayer, Christian ; Tariq, Muhammad Adnan ; Rothermel, Kurt:
Graphcep : Real-time data analytics using parallel complex event and graph processing.
In: Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems. - New York : Association for Computing Machinery , 2016 . - pp. 309-316
ISBN 978-1-4503-4021-2
DOI: https://doi.org/10.1145/2933267.2933509

Abstract in another language

In recent years, the proliferation of highly dynamic graph-structured data streams fueled the demand for real-time data analytics. For instance, detecting recent trends in social networks enables new applications in areas such as disaster detection, business analytics or health-care. Parallel Complex Event Processing has evolved as the paradigm of choice to analyze data streams in a timely manner, where the incoming data streams are split and processed independently by parallel operator instances. However, the degree of parallelism is limited by the feasibility of splitting the data streams into independent parts such that correctness of event processing is still ensured. In this paper, we overcome this limitation for graph-structured data by further parallelizing individual operator instances using modern graph processing systems. These systems partition the graph data and execute graph algorithms in a highly parallel fashion, for instance using cloud resources. To this end, we propose a novel graph-based Complex Event Processing system GraphCEP and evaluate its performance in the setting of two case studies from the DEBS Grand Challenge 2016.

Further data

Item Type: Article in a book
Refereed: Yes
Institutions of the University: Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Data Systems > Chair Data Systems - Univ.-Prof. Dr. Ruben Mayer
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 25 Apr 2023 11:53
Last Modified: 05 Feb 2024 07:45
URI: https://eref.uni-bayreuth.de/id/eprint/76017