Exact Monte Carlo simulation for fork-join networks

DAI, HONGSHENG (2011) Exact Monte Carlo simulation for fork-join networks Advances In Applied Probability, 43 (2). ISSN 0001-8678

Full text not available from this repository.

Official URL: http://projecteuclid.org/euclid.aap/1308662489

Abstract

In a fork-join network each incoming job is split into K tasks and the K tasks are simultaneously assigned to $K$ 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.

Item Type:Journal article
Uncontrolled Keywords:Coupling from the past; fork-join network; perfect sampling; read-once coupling from the past
Subjects:G000 Computing and Mathematical Sciences > G100 Mathematics
G000 Computing and Mathematical Sciences > G400 Computing
Faculties:Faculty of Science and Engineering > School of Computing, Engineering and Mathematics > Computational Mathematics
Related URLs:
ID Code:9783
Deposited By:Converis
Deposited On:26 Jan 2012 10:26
Last Modified:09 Jan 2013 07:38

Repository Staff Only: item control page