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TOMACS
2010

State-dependent importance sampling for a Jackson tandem network

9 years 10 months ago
State-dependent importance sampling for a Jackson tandem network
This paper considers importance sampling as a tool for rare-event simulation. The focus is on estimating the probability of overflow in the downstream queue of a Jacksonian two-node tandem queue – it is known that in this setting ‘traditional’ stateindependent importance-sampling distributions perform poorly. We therefore concentrate on developing a state-dependent change of measure, that we prove to be asymptotically efficient. More specific contributions are the following. (i) We concentrate on the probability of the second queue exceeding a certain predefined threshold before the system empties. Importantly, we identify an asymptotically efficient importance-sampling distribution for any initial state of the system. (ii) The choice of the importance-sampling distribution is backed up by appealing heuristics that are rooted in large-deviations theory. (iii) Our method for proving asymptotic efficiency is substantially more straightforward than some that have been used ea...
Denis I. Miretskiy, Werner R. W. Scheinhardt, Mich
Added 31 Jan 2011
Updated 31 Jan 2011
Type Journal
Year 2010
Where TOMACS
Authors Denis I. Miretskiy, Werner R. W. Scheinhardt, Michel Mandjes
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