Bellman, K, Botev, J, Diaconescu, A et al. (8 more authors) (2021) Self-improving system integration: Mastering continuous change. Future Generation Computer Systems, 117. pp. 29-46. ISSN 0167-739X
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier B.V. All rights reserved. This is an author produced version of an article published in Future Generation Computer Systems. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Self-integration; Self-improvement; Autonomous systems; Taxonomy; Organic computing; System engineering |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Apr 2021 09:20 |
Last Modified: | 24 Nov 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.future.2020.11.019 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:173338 |