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Authors: Paul A. Akiki ; Andrea Zisman and Amel Bennaceur

Affiliation: School of Computing and Communications, The Open University, Milton Keynes, U.K.

Keyword(s): Task Modelling Notation, Resource-driven Adaptation, Enterprise System.

Abstract: Enterprise Systems (ESs) can make use of tasks that depend on various types of resources such as robots and raw materials. The variability of resources can cause losses to enterprises. For example, the malfunctioning of robots at automated warehouses could delay product deliveries and cause financial losses. These losses can be avoided if resource-driven adaptation is supported. In order to support resource-driven adaptation in ESs, this paper presents a task modelling notation called SERIES, which is used for specifying the tasks of ESs at design time and the enterprise-specific task variants and property values at runtime. SERIES is complemented by a visual tool. We assessed the usability of SERIES using the cognitive dimensions framework. We also evaluated SERIES by developing resource-driven adaptation examples and measuring the performance overhead and source-code intrusiveness. The results showed that SERIES does not hinder performance and is non-intrusive.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Akiki, P.; Zisman, A. and Bennaceur, A. (2022). SERIES: A Task Modelling Notation for Resource-driven Adaptation. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-569-2; ISSN 2184-4992, SciTePress, pages 29-39. DOI: 10.5220/0011001800003179

@conference{iceis22,
author={Paul A. Akiki. and Andrea Zisman. and Amel Bennaceur.},
title={SERIES: A Task Modelling Notation for Resource-driven Adaptation},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2022},
pages={29-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011001800003179},
isbn={978-989-758-569-2},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - SERIES: A Task Modelling Notation for Resource-driven Adaptation
SN - 978-989-758-569-2
IS - 2184-4992
AU - Akiki, P.
AU - Zisman, A.
AU - Bennaceur, A.
PY - 2022
SP - 29
EP - 39
DO - 10.5220/0011001800003179
PB - SciTePress

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