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Authors: Arne Koschel 1 ; Irina Astrova 2 ; Anna Pakosch 1 ; Christian Gerner 1 ; Christin Schulze 1 and Matthias Tyca 1

Affiliations: 1 Hochschule Hannover, DataH, University of Applied Sciences and Arts, Hannover, Germany ; 2 Department of Software Science, School of IT, Tallinn University of Technology, Tallinn, Estonia

Keyword(s): Event Processing Network (EPN), Event Processing Network Model, Amazon Kinesis Data Analytics.

Abstract: This article looks at a proposed list of generalized requirements for a unified modelling of event processing networks (EPNs) and its application to Amazon Kinesis Data Analytics. It enhances our previous work in this area, in which we recently analyzed Apache Storm and earlier also the EPiA model, the BEMN model, and the RuleCore model. Our proposed EPN requirements look at both: The logical model of EPNs and the concrete technical implementation of them. Therefore, our article provides requirements for EPN models based on attributes derived from event processing in general as well as existing models. Moreover, as its core contribution, our article applies those requirements by an in depth analysis of Amazon Kinesis Data Analytics as a concrete implementation foundation of an EPN model.

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Paper citation in several formats:
Koschel, A.; Astrova, I.; Pakosch, A.; Gerner, C.; Schulze, C. and Tyca, M. (2024). Is Amazon Kinesis Data Analytics Suitable as Core for an Event Processing Network Model?. In Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-680-4; ISSN 2184-433X, SciTePress, pages 1036-1043. DOI: 10.5220/0012432800003636

@conference{icaart24,
author={Arne Koschel. and Irina Astrova. and Anna Pakosch. and Christian Gerner. and Christin Schulze. and Matthias Tyca.},
title={Is Amazon Kinesis Data Analytics Suitable as Core for an Event Processing Network Model?},
booktitle={Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2024},
pages={1036-1043},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012432800003636},
isbn={978-989-758-680-4},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Is Amazon Kinesis Data Analytics Suitable as Core for an Event Processing Network Model?
SN - 978-989-758-680-4
IS - 2184-433X
AU - Koschel, A.
AU - Astrova, I.
AU - Pakosch, A.
AU - Gerner, C.
AU - Schulze, C.
AU - Tyca, M.
PY - 2024
SP - 1036
EP - 1043
DO - 10.5220/0012432800003636
PB - SciTePress

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