MTTF Estimation Using Importance Sampling on Markov Models - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Research Report) Year : 1999

MTTF Estimation Using Importance Sampling on Markov Models


Very complex systems occur nowadays quite frequently in many technological areas and they are often required to comply with high dependability standards. To study their availability and reliability characteristics, Markovian models are commonly used. Due to the size and complexity of the systems, and due to the rarity of system failures, both analytical solutions and "crude" simulation can be inefficient or even non-relevant. A number of variance reduction Monte Carlo techniques have been proposed to overcome this difficulty; importance sampling methods are among the most efficient. The objective of this paper is to survey existing importance sampling schemes, to propose some improvements and to discuss on their different properties.
Fichier principal
Vignette du fichier
RR-3672.pdf (323.57 Ko) Télécharger le fichier

Dates and versions

inria-00073000 , version 1 (24-05-2006)


  • HAL Id : inria-00073000 , version 1


Héctor Cancela, Gerardo Rubino, Bruno Tuffin. MTTF Estimation Using Importance Sampling on Markov Models. [Research Report] RR-3672, INRIA. 1999. ⟨inria-00073000⟩
289 View
205 Download


Gmail Facebook Twitter LinkedIn More