Asymptotic optimality of RESTART estimators in highly dependable systems

Villén Altamirano, José (2014). Asymptotic optimality of RESTART estimators in highly dependable systems. "Reliability Engineering & System Safety", v. 130 ; pp. 115-124. ISSN 0951-8320. https://doi.org/10.1016/j.ress.2014.05.012.

Descripción

Título: Asymptotic optimality of RESTART estimators in highly dependable systems
Autor/es:
  • Villén Altamirano, José
Tipo de Documento: Artículo
Título de Revista/Publicación: Reliability Engineering & System Safety
Fecha: Octubre 2014
Volumen: 130
Materias:
Palabras Clave Informales: Rare event, RESTART simulation,subset simulation, reliability, HRMS systems,asymptotic optimality
Escuela: E.T.S.I. de Sistemas Informáticos (UPM)
Departamento: Matemática Aplicada a las Tecnologías de la Información y las Comunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Abstract We consider a wide class of models that includes the highly reliable Markovian systems (HRMS) often used to represent the evolution of multi-component systems in reliability settings. Repair times and component lifetimes are random variables that follow a general distribution, and the repair service adopts a priority repair rule based on system failure risk. Since crude simulation has proved to be inefficient for highly-dependable systems, the RESTART method is used for the estimation of steady-state unavailability and other reliability measures. In this method, a number of simulation retrials are performed when the process enters regions of the state space where the chance of occurrence of a rare event (e.g., a system failure) is higher. The main difficulty involved in applying this method is finding a suitable function, called the importance function, to define the regions. In this paper we introduce an importance function which, for unbalanced systems, represents a great improvement over the importance function used in previous papers. We also demonstrate the asymptotic optimality of RESTART estimators in these models. Several examples are presented to show the effectiveness of the new approach, and probabilities up to the order of 10-42 are accurately estimated with little computational effort.

Proyectos asociados

TipoCódigoAcrónimoResponsableTítulo
Gobierno de EspañaMYTM2011-28983-C03-03Sin especificarSin especificarSin especificar
Comunidad de MadridS2009/ESP-1685Sin especificarSin especificarSin especificar

Más información

ID de Registro: 37455
Identificador DC: http://oa.upm.es/37455/
Identificador OAI: oai:oa.upm.es:37455
Identificador DOI: 10.1016/j.ress.2014.05.012
URL Oficial: http://www.sciencedirect.com/science/article/pii/S0951832014001227
Depositado por: Memoria Investigacion
Depositado el: 09 Mar 2016 19:29
Ultima Modificación: 09 Mar 2016 19:29
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