@inproceedings{2fe393bd2de74b988c2cafe6b6507c37,
title = "SERIES: A Task Modelling Notation for Resource-driven Adaptation",
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.",
keywords = "Enterprise System, Resource-driven Adaptation, Task Modelling Notation",
author = "Akiki, \{Paul A.\} and Andrea Zisman and Amel Bennaceur",
note = "Publisher Copyright: Copyright {\textcopyright} 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.; 24th International Conference on Enterprise Information Systems, ICEIS 2022 ; Conference date: 25-04-2022 Through 27-04-2022",
year = "2022",
doi = "10.5220/0011001800003179",
language = "English",
series = "International Conference on Enterprise Information Systems, ICEIS - Proceedings",
publisher = "Science and Technology Publications, Lda",
pages = "29--39",
editor = "Joaquim Filipe and Michal Smialek and Alexander Brodsky and Slimane Hammoudi",
booktitle = "Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2, ICEIS 2022",
}