Göttmann, Hendrik ; Caesar, Birte ; Beers, Lasse ; Lochau, Malte ; Schürr, Andy ; Fay, Alexander (2024)
Cost-sensitive precomputation of real-time-aware reconfiguration strategies based on stochastic priced timed games.
In: Software and Systems Modeling, 2024
doi: 10.1007/s10270-024-01195-9
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
In many recent application domains, software systems must repeatedly reconfigure themselves at runtime to satisfy changing contextual requirements. To decide which next configuration is presumably best suited is a very challenging task as it involves not only functional requirements but also non-functional properties (NFP). NFP include multiple, potentially contradicting, criteria like real-time constraints and cost measures like energy consumption. Effectiveness of context-aware reconfiguration decisions further depends on mostly uncertain future contexts which makes greedy one-step decision heuristics potentially misleading. Moreover, the computational runtime overhead for reconfiguration planning should not nullify the benefits. Nevertheless, entirely pre-planning reconfiguration decisions during design time is also not feasible due to missing knowledge about runtime contexts. In this article, we propose a model-based technique for precomputing context-aware reconfiguration decisions under partially uncertain real-time constraints and cost measures. We employ a game-theoretic approach based on stochastic priced timed game automata as reconfiguration model. This formal model allows us to automatically synthesize winning strategies for the first player (the system) which efficiently delivers presumably best-fitting reconfiguration decisions as reactions to moves of the second player (the context) at runtime. Our tool implementation copes with the high computational complexity of strategy synthesis by utilizing the statistical model checker Uppaal Stratego to approximate near-optimal solutions. We applied our tool to a real-world example consisting of a reconfigurable robot support system for the construction of aircraft fuselages. Our evaluation results show that Uppaal Stratego is indeed able to precompute effective reconfiguration strategies within a reasonable amount of time.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Göttmann, Hendrik ; Caesar, Birte ; Beers, Lasse ; Lochau, Malte ; Schürr, Andy ; Fay, Alexander |
| Art des Eintrags: | Bibliographie |
| Titel: | Cost-sensitive precomputation of real-time-aware reconfiguration strategies based on stochastic priced timed games |
| Sprache: | Englisch |
| Publikationsjahr: | 5 August 2024 |
| Verlag: | Springer |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Software and Systems Modeling |
| Jahrgang/Volume einer Zeitschrift: | 2024 |
| Kollation: | 31 Seiten |
| DOI: | 10.1007/s10270-024-01195-9 |
| Kurzbeschreibung (Abstract): | In many recent application domains, software systems must repeatedly reconfigure themselves at runtime to satisfy changing contextual requirements. To decide which next configuration is presumably best suited is a very challenging task as it involves not only functional requirements but also non-functional properties (NFP). NFP include multiple, potentially contradicting, criteria like real-time constraints and cost measures like energy consumption. Effectiveness of context-aware reconfiguration decisions further depends on mostly uncertain future contexts which makes greedy one-step decision heuristics potentially misleading. Moreover, the computational runtime overhead for reconfiguration planning should not nullify the benefits. Nevertheless, entirely pre-planning reconfiguration decisions during design time is also not feasible due to missing knowledge about runtime contexts. In this article, we propose a model-based technique for precomputing context-aware reconfiguration decisions under partially uncertain real-time constraints and cost measures. We employ a game-theoretic approach based on stochastic priced timed game automata as reconfiguration model. This formal model allows us to automatically synthesize winning strategies for the first player (the system) which efficiently delivers presumably best-fitting reconfiguration decisions as reactions to moves of the second player (the context) at runtime. Our tool implementation copes with the high computational complexity of strategy synthesis by utilizing the statistical model checker Uppaal Stratego to approximate near-optimal solutions. We applied our tool to a real-world example consisting of a reconfigurable robot support system for the construction of aircraft fuselages. Our evaluation results show that Uppaal Stratego is indeed able to precompute effective reconfiguration strategies within a reasonable amount of time. |
| Zusätzliche Informationen: | Special Section Paper |
| Fachbereich(e)/-gebiet(e): | 18 Fachbereich Elektrotechnik und Informationstechnik 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik > Echtzeitsysteme 18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Datentechnik DFG-Sonderforschungsbereiche (inkl. Transregio) DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > A: Konstruktionsmethodik DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > A: Konstruktionsmethodik > Teilprojekt A4: Selbst-Adaption |
| Hinterlegungsdatum: | 14 Aug 2024 10:47 |
| Letzte Änderung: | 08 Nov 2024 07:56 |
| PPN: | 523419899 |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
 |
Frage zum Eintrag |
Optionen (nur für Redakteure)
 |
Redaktionelle Details anzeigen |
Drucken
Impressum