International Journal of Computational Intelligence Systems

Volume 11, Issue 1, 2018, Pages 272 - 281

An architecture based on computing with words to support runtime reconfiguration decision of service-based systems

Authors
Romina Torres1, romina.torres@unab.cl, Rodrigo Salas2, rodrigo.salas@uv.cl, Nelly Bencomo3, n.bencomo@aston.ac.uk, Hernan Astudillo4, hernan@inf.utfsm.cl
1Faculty of Engineering Universidad Andres Bello, Viña del Mar, Chile
2Biomedical Engineering School, Universidad de Valparaiso, Valparaíso, Chile
3School of Engineering and Applied Science, Aston University, Birmingham, UK
4Informatics Department, Universidad Técnica Federico Santa María, Valparaíso, Chile
Received 20 October 2017, Accepted 27 October 2017, Available Online 1 January 2018.
DOI
https://doi.org/10.2991/ijcis.11.1.21How to use a DOI?
Keywords
service-based systems; quality-of-service; linguistic decision making models; computing with words
Abstract

Service-based systems (SBSs) need to be reconfigured when there is evidence that the selected Web services configurations no further satisfy the specifications models and, thus the decision-related models will need to be updated accordingly. However, such updates need to be performed at the right pace. On the one hand, if the updates are not quickly enough, the reconfigurations that are required may not be detected due to the obsolescence of the specification models used at runtime, which were specified at design-time. On the other hand, the other extreme is to promote premature reconfiguration decisions that are based on models that may be highly sensitive to environmental fluctuations and which may affect the stability of these systems. To deal with the required trade-offs of this situation, this paper proposes the use of linguistic decision-making (LDM) models to represent specification models of SBSs and a dynamic computing-with-words (CWW) architecture to dynamically assess the models by using a multi-period multi-attribute decision making (MP-MADM) approach. The proposed solution allows systems under dynamic environments to offer improved system stability by better managing the trade-off between the potential obsolescence of the specification models, and the required dynamic sensitivity and update of these models.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
11 - 1
Pages
272 - 281
Publication Date
2018/01/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
https://doi.org/10.2991/ijcis.11.1.21How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Romina Torres
AU  - Rodrigo Salas
AU  - Nelly Bencomo
AU  - Hernan Astudillo
PY  - 2018
DA  - 2018/01/01
TI  - An architecture based on computing with words to support runtime reconfiguration decision of service-based systems
JO  - International Journal of Computational Intelligence Systems
SP  - 272
EP  - 281
VL  - 11
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.11.1.21
DO  - https://doi.org/10.2991/ijcis.11.1.21
ID  - Torres2018
ER  -