Synthesis of Optimal Resilient Control Strategies

D 2017

Synthesis of Optimal Resilient Control Strategies

BAIER, Christel, Clemens DUBSLAFF, Ľuboš KORENČIAK, Antonín KUČERA, Vojtěch ŘEHÁK et. al.

Basic information

Original name

Synthesis of Optimal Resilient Control Strategies

Authors

BAIER, Christel (276 Germany), Clemens DUBSLAFF (276 Germany), Ľuboš KORENČIAK (703 Slovakia, guarantor, belonging to the institution), Antonín KUČERA (203 Czech Republic, belonging to the institution) and Vojtěch ŘEHÁK (203 Czech Republic, belonging to the institution)

Edition

Cham, Automated Technology for Verification and Analysis, p. 417-434, 18 pp. 2017

Publisher

Springer International Publishing

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/17:00095082

Organization unit

Faculty of Informatics

ISBN

978-3-319-68166-5

ISSN

DOI

http://dx.doi.org/10.1007/978-3-319-68167-2_27

UT WoS

000723567800027

Keywords in English

controller synthesis; Markov decision processes; resilience

Abstract

V originále

Repair mechanisms are important within resilient systems to maintain the system in an operational state after an error occurred. Usually, constraints on the repair mechanisms are imposed, e.g., concerning the time or resources required (such as energy consumption or other kinds of costs). For systems modeled by Markov decision processes (MDPs), we introduce the concept of resilient schedulers, which represent control strategies guaranteeing that these constraints are always met within some given probability. Assigning rewards to the operational states of the system, we then aim towards resilient schedulers which maximize the long-run average reward, i.e., the expected mean payoff. We present a pseudo-polynomial algorithm that decides whether a resilient scheduler exists and if so, yields an optimal resilient scheduler. We show also that already the decision problem asking whether there exists a resilient scheduler is PSPACE-hard.

Links

GA15-17564S, research and development project

Name: Teorie her jako prostředek pro formální analýzu a verifikaci počítačových systémů

Investor: Czech Science Foundation

MUNI/A/0992/2016, interní kód MU

Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity (Acronym: SKOMU)

Investor: Masaryk University, Category A

Citovat

BAIER, Christel, Clemens DUBSLAFF, Ľuboš KORENČIAK, Antonín KUČERA and Vojtěch ŘEHÁK. Synthesis of Optimal Resilient Control Strategies. In Deepak D'Souza, K. Narayan Kumar. Automated Technology for Verification and Analysis. Cham: Springer International Publishing, 2017, p. 417-434. ISBN 978-3-319-68166-5. Available from: https://dx.doi.org/10.1007/978-3-319-68167-2_27.

@inproceedings{1392977,
   author = {Baier, Christel and Dubslaff, Clemens and Korenčiak, Ľuboš and Kučera, Antonín and Řehák, Vojtěch},
   address = {Cham},
   booktitle = {Automated Technology for Verification and Analysis},
   doi = {http://dx.doi.org/10.1007/978-3-319-68167-2_27},
   editor = {Deepak D'Souza, K. Narayan Kumar},
   keywords = {controller synthesis; Markov decision processes; resilience},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Cham},
   isbn = {978-3-319-68166-5},
   pages = {417-434},
   publisher = {Springer International Publishing},
   title = {Synthesis of Optimal Resilient Control Strategies},
   year = {2017}
}

TY  - JOUR
ID  - 1392977
AU  - Baier, Christel - Dubslaff, Clemens - Korenčiak, Ľuboš - Kučera, Antonín - Řehák, Vojtěch
PY  - 2017
TI  - Synthesis of Optimal Resilient Control Strategies
PB  - Springer International Publishing
CY  - Cham
SN  - 9783319681665
KW  - controller synthesis
KW  - Markov decision processes
KW  - resilience
N2  - Repair mechanisms are important within resilient systems to maintain the system in an operational state after an error occurred. Usually, constraints on the repair mechanisms are imposed, e.g., concerning the time or resources required (such as energy consumption or other kinds of costs). For systems modeled by Markov decision processes (MDPs), we introduce the concept of resilient schedulers, which represent control strategies guaranteeing that these constraints are always met within some given probability. Assigning rewards to the operational states of the system, we then aim towards resilient schedulers which maximize the long-run average reward, i.e., the expected mean payoff. We present a pseudo-polynomial algorithm that decides whether a resilient scheduler exists and if so, yields an optimal resilient scheduler. We show also that already the decision problem asking whether there exists a resilient scheduler is PSPACE-hard.
ER  -

BAIER, Christel, Clemens DUBSLAFF, Ľuboš KORENČIAK, Antonín KUČERA and Vojtěch ŘEHÁK. Synthesis of Optimal Resilient Control Strategies. In Deepak D'Souza, K. Narayan Kumar. \textit{Automated Technology for Verification and Analysis}. Cham: Springer International Publishing, 2017, p.~417-434. ISBN~978-3-319-68166-5. Available from: https://dx.doi.org/10.1007/978-3-319-68167-2\_{}27.

Detailed Information on Publication Record