Self-improving system integration:Mastering continuous change

Abstract

The research initiative “self-improving system integration” (SISSY) was established with the goal to master the ever-changing demands of system organisation in the presence of autonomous subsystems, evolving architectures, and highly-dynamic open environments. It aims to move integration-related decisions from design-time to run-time, implying a further shift of expertise and responsibility from human engineers to autonomous systems. This introduces a qualitative shift from existing self-adaptive and self-organising systems, moving from self-adaptation based on predefined variation types, towards more open contexts involving novel autonomous subsystems, collaborative behaviours, and emerging goals. In this article, we revisit existing SISSY research efforts and establish a corresponding terminology focusing on how SISSY relates to the broad field of integration sciences. We then investigate SISSY-related research efforts and derive a taxonomy of SISSY technology. This is concluded by establishing a research road-map for developing operational self-improving self-integrating systems.

Publication DOI: https://doi.org/10.1016/j.future.2020.11.019
Divisions: College of Engineering & Physical Sciences > Aston Institute of Urban Technology and the Environment (ASTUTE)
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Funding Information: Lukas Esterle s an Assistant Professor in Electrical and Computer Engineering at Aarhus University, Denmark. Lukas holds a Masters degree in Computer Science and a Dr.-techn. in Electrical Engineering from Alpen-Adria University Klagenfurt. He was a postd
Additional Information: © 2020, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Funding Information: Lukas Esterle s an Assistant Professor in Electrical and Computer Engineering at Aarhus University, Denmark. Lukas holds a Masters degree in Computer Science and a Dr.-techn. in Electrical Engineering from Alpen-Adria University Klagenfurt. He was a postdoctoral researcher at the University of Technology in Vienna and a Marie Skłodowska Curie Fellow at Aston University, Birmingham, UK funded by the European Commission. His research interests are collaborative, autonomous, and self-aware systems, Computational and Artificial Intelligence, multi-agent and cyberphysical systems, and nature-inspired approaches to solve complex problems. Lukas co-authored several books on Self-aware computing systems and made substantial contributions to several self-aware computing applications around visual sensor networks and multi-robot systems. Lukas is a member of the Aarhus University Centre for Digitalisation, Big Data and Data Analytics (DIGIT) Publisher Copyright: © 2020 Elsevier B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
Uncontrolled Keywords: Autonomous systems,Organic computing,Self-improvement,Self-integration,System engineering,Taxonomy,Software,Hardware and Architecture,Computer Networks and Communications
Publication ISSN: 1872-7115
Last Modified: 19 Mar 2024 08:21
Date Deposited: 09 Dec 2020 12:44
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 0430?via%3Dihub (Publisher URL)
PURE Output Type: Article
Published Date: 2021-04-01
Published Online Date: 2020-11-24
Accepted Date: 2020-11-19
Authors: Bellman, Kirstie
Botev, Jean
Diaconescu, Ada
Esterle, Lukas
Gruhl, Christian
Landauer, Christopher
Lewis, Peter R. (ORCID Profile 0000-0003-4271-8611)
Nelson, Phyllis R.
Pournaras, Evangelos
Stein, Anthony
Tomforde, Sven

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