SERIES: A Task Modelling Notation for Resource-driven Adaptation

Paul Akiki, Andrea Zisman, Amel Bennaceur

2022

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.

Paper Citation

in Harvard Style

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 1: ICEIS, ISBN 978-989-758-569-2, pages 29-39. DOI: 10.5220/0011001800003179

in Bibtex Style

@conference{iceis22,
author={Paul 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 1: ICEIS,},
year={2022},
pages={29-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011001800003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - SERIES: A Task Modelling Notation for Resource-driven Adaptation
SN - 978-989-758-569-2
AU - Akiki P.
AU - Zisman A.
AU - Bennaceur A.
PY - 2022
SP - 29
EP - 39
DO - 10.5220/0011001800003179