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

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandBeitrag in Buch/SammelwerkForschungPeer-Review

Autoren

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

Organisationseinheiten

Externe Organisationen

  • Universität Kassel
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Herausgeber/-innenNgoc Thanh Nguyen, Ryszard Kowalczyk, Jaap van den Herik, Ana Paula Rocha, Joaquim Filipe
Herausgeber (Verlag)Springer Verlag
Seiten193-220
Seitenumfang28
ISBN (elektronisch)9783319783017
ISBN (Print)9783319783000
PublikationsstatusVeröffentlicht - 2018

Publikationsreihe

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band10780 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)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 Sachgebiete

Zitieren

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). Hrsg. / Ngoc Thanh Nguyen; Ryszard Kowalczyk; Jaap van den Herik; Ana Paula Rocha; Joaquim Filipe. Springer Verlag, 2018. S. 193-220 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 10780 LNCS).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandBeitrag in Buch/SammelwerkForschungPeer-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 (Hrsg.), 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), Bd. 10780 LNCS, Springer Verlag, S. 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 (Hrsg.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (S. 193-220). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 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, Hrsg., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018. S. 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). Hrsg. / Ngoc Thanh Nguyen ; Ryszard Kowalczyk ; Jaap van den Herik ; Ana Paula Rocha ; Joaquim Filipe. Springer Verlag, 2018. S. 193-220 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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