Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness: A generalised approach for the quantification of robustness

Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review

Authors

  • Sven Tomforde
  • Jan Kantert
  • Christian Müller-Schloer
  • Sebastian Bödelt
  • Bernhard Sick

Research Organisations

External Research Organisations

  • University of Kassel
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Details

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsNgoc Thanh Nguyen, Ryszard Kowalczyk, Jaap van den Herik, Ana Paula Rocha, Joaquim Filipe
PublisherSpringer Verlag
Pages193-220
Number of pages28
ISBN (electronic)9783319783017
ISBN (print)9783319783000
Publication statusPublished - 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10780 LNCS
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

Self-adaptation and self-organisation (SASO) are increasingly used in information and communication technology to master complexity and keep the administrative effort at an acceptable level. However, using SASO mechanisms is not an end in itself – the primary goal is typically to allow for a higher autonomy of systems in order to react appropriately to disturbances and dynamics in the environmental conditions. We refer to this goal as achieving “robustness”. During design-time, engineers have different possibilities to develop SASO mechanisms for an underlying control problem. When deciding which path to follow, an analysis of the inherent robustness of possible solutions is necessary. In this article, we present a novel quantification method for robustness that provides the basis to compare different control strategies in similar conditions.

ASJC Scopus subject areas

Cite this

Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness: A generalised approach for the quantification of robustness. / Tomforde, Sven; Kantert, Jan; Müller-Schloer, Christian et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). ed. / Ngoc Thanh Nguyen; Ryszard Kowalczyk; Jaap van den Herik; Ana Paula Rocha; Joaquim Filipe. Springer Verlag, 2018. p. 193-220 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10780 LNCS).

Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review

Tomforde, S, Kantert, J, Müller-Schloer, C, Bödelt, S & Sick, B 2018, Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness: A generalised approach for the quantification of robustness. in NT Nguyen, R Kowalczyk, J van den Herik, AP Rocha & J Filipe (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10780 LNCS, Springer Verlag, pp. 193-220. https://doi.org/10.1007/978-3-319-78301-7_9
Tomforde, S., Kantert, J., Müller-Schloer, C., Bödelt, S., & Sick, B. (2018). Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness: A generalised approach for the quantification of robustness. In N. T. Nguyen, R. Kowalczyk, J. van den Herik, A. P. Rocha, & J. Filipe (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 193-220). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10780 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-78301-7_9
Tomforde S, Kantert J, Müller-Schloer C, Bödelt S, Sick B. Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness: A generalised approach for the quantification of robustness. In Nguyen NT, Kowalczyk R, van den Herik J, Rocha AP, Filipe J, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018. p. 193-220. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2018 Apr 14. doi: 10.1007/978-3-319-78301-7_9
Tomforde, Sven ; Kantert, Jan ; Müller-Schloer, Christian et al. / Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness : A generalised approach for the quantification of robustness. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). editor / Ngoc Thanh Nguyen ; Ryszard Kowalczyk ; Jaap van den Herik ; Ana Paula Rocha ; Joaquim Filipe. Springer Verlag, 2018. pp. 193-220 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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