dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.contributor
Universitat Politècnica de Catalunya. QINE - Disseny de Baix Consum, Test, Verificació i Circuits Integrats de Seguretat
dc.contributor.author
Carrasco, Juan A.
dc.identifier
Carrasco, J. Analysis of sparse numerical methods for dependability evaluation. A: IASTED International Symposium Identification, Modeling and Simulation. "Identification, modelling and simulation: Paris, France, June 22-24, 1987". ACTA Press, 1987, p. 437-441.
dc.identifier
https://hdl.handle.net/2117/23545
dc.description.abstract
Homogeneous, continuous-time Markov chains are an usual mathematical tool for dependability evaluation of computer systems. Complex systems rise the large state space problem, thus making mandatory the use of efficient numerical methods. This paper analyzes state of the art sparse methods in the context of the development of an enhanced version of an existing tool. We first consider point SOR for the evaluation of the stationary probability and mean time before absorption vectors. By dynamic adjustment of the relaxation parameter a very high convergence rate is attained in many cases. The convergence rate is however rather poor when the Markov chain contains highly recurrent subsets. In order to improve the method we propose the integration of a novel, exact, one-step aggregation technique with block SOR. For the evaluation of the transient regime, two methods are compared: randomization and implicit integration. Scenarios in which one of them is clearly preferable are described.
dc.description.abstract
Postprint (published version)
dc.format
application/pdf
dc.subject
Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació
dc.subject
Fault-tolerant computing
dc.subject
Tolerància als errors (Informàtica)
dc.title
Analysis of sparse numerical methods for dependability evaluation
dc.type
Conference report
