Research Repository

Exact Monte Carlo simulation for fork-join networks

Dai, H (2011) 'Exact Monte Carlo simulation for fork-join networks.' Advances in Applied Probability, 43 (2). 484 - 503. ISSN 0001-8678

Full text not available from this repository.


In a fork-join network each incoming job is split into K tasks and the K tasks are simultaneously assigned toK parallel service stations for processing. For the distributions of response times and queue lengths of fork-join networks, no explicit formulae are available. Existing methods provide only analytic approximations for the response time and the queue length distributions. The accuracy of such approximations may be difficult to justify for some complicated fork-join networks. In this paper we propose a perfect simulation method based on coupling from the past to generate exact realisations from the equilibrium of fork-join networks. Using the simulated realisations, Monte Carlo estimates for the distributions of response times and queue lengths of fork-join networks are obtained. Comparisons of Monte Carlo estimates and theoretical approximations are also provided. The efficiency of the sampling algorithm is shown theoretically and via simulation. © 2011 Applied Probability Trust.

Item Type: Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Jim Jamieson
Date Deposited: 12 Feb 2013 07:44
Last Modified: 04 Feb 2019 16:15

Actions (login required)

View Item View Item