Title :
Parametric NdRFT for the derivation of optimal repair strategies
Author :
Beccuti, M. ; Franceschinis, G. ; Codetta-Raiteri, Daniele ; Haddad, Sandro
Author_Institution :
DI, Univ. del Piemonte Orientale, Alessandria, Italy
fDate :
June 29 2009-July 2 2009
Abstract :
Non deterministic Repairable Fault Trees (NdRFT) are a recently proposed modeling formalism for the study of optimal repair strategies: they are based on the widely adopted Fault Tree formalism, but in addition to the failure modes, NdRFTs allow to define possible repair actions. In a previous pa per the formalism has been introduced together with an analysis method and a tool allowing to automatically derive the best repair strategy to be applied in each state. The analysis technique is based on the generation and solution of a Markov Decision Process. In this paper we present an extension, ParNdRFT, that allows to exploit the presence of redundancy to reduce the complexity of the model and of the analysis. It is based on the translation of the ParNdRFT in to a Markov Decision Well-Formed Net, i.e. a model specified by means of an High Level Petri Net formalism. The translated model can be efficiently solved thanks to existing algorithms that generate a reduced state space automatically exploiting the model symmetries.
Keywords :
Markov processes; Petri nets; consecutive system reliability; fault trees; Markov decision process; failure modes; fault tree formalism; high level Petri net formalism; nondeterministic repairable fault trees; optimal repair strategies; repair actions; Algorithm design and analysis; Failure analysis; Fault trees; Petri nets; Redundancy; Reliability; Software measurement; Software tools; State-space methods; Time measurement; Fault Trees; Markov Decision Process; Optimal repair strategy; Symmetries; Well-Formed Nets;
Conference_Titel :
Dependable Systems & Networks, 2009. DSN '09. IEEE/IFIP International Conference on
Conference_Location :
Lisbon
Print_ISBN :
978-1-4244-4422-9
Electronic_ISBN :
978-1-4244-4421-2
DOI :
10.1109/DSN.2009.5270312