Attaining Meta-Self-Awareness Through Assessment of Quality-of-Knowledge

Elhabbash, A., Bahsoon, R., Tino, P., Lewis, P. and Elkhatib, Y. (2021) Attaining Meta-Self-Awareness Through Assessment of Quality-of-Knowledge. In: 2021 IEEE International Conference on Web Services (ICWS), Chicago, IL, USA, 05-10 Sep 2021, pp. 712-723. ISBN 9781665416818 (doi: 10.1109/ICWS53863.2021.00099)

[img] Text
249212.pdf - Accepted Version



Self-awareness is a crucial capability of autonomous service-based systems that enables them to self-adapt. There are different types of self-awareness whereby certain types of knowledge are captured at various levels. We argue that effective management of the trade-offs of dependability requirements can be achieved through “seamless” switching between different levels of awareness. However, the assessment of the quality of knowledge to enable dynamic switching between self-awareness levels has not been tackled yet. We propose a general architecture that exploits symbiotic simulation in order to tackle the complexity of assessing the quality of knowledge and attaining the meta-self-awareness property, wherein the system can reflect on its different levels of awareness. We conduct a thorough real-world study in the context of volunteer services. We conclude that a system made meta-self-aware using our approach achieves optimal performance by activating the most suitable awareness level. This comes at the cost of a modest computational overhead.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Elkhatib, Dr Yehia
Authors: Elhabbash, A., Bahsoon, R., Tino, P., Lewis, P., and Elkhatib, Y.
Subjects:Q Science > QA Mathematics > QA76 Computer software
College/School:College of Science and Engineering > School of Computing Science
Published Online:15 November 2021
Copyright Holders:Copyright © 2021 IEEE
Publisher Policy:Reproduced in accordance with the publisher copyright policy
Related URLs:

University Staff: Request a correction | Enlighten Editors: Update this record