Bias in parallel and distributed simulation systems
Even after several decades of research, modeling is considered an art, with a high liability to produce incorrect abstractions of real world systems. Therefore, validation and verification of simulation models is considered an indispensable method to establish the credibility of developed models. In...
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creator | Kiesling, T. Khayari, R.E.A. Luthi, J. |
description | Even after several decades of research, modeling is considered an art, with a high liability to produce incorrect abstractions of real world systems. Therefore, validation and verification of simulation models is considered an indispensable method to establish the credibility of developed models. In the process of parallelizing or distributing a given credible simulation model, a bias is introduced, possibly leading to serious errors in simulation results. Depending on the mechanisms used for parallelization or distribution, a separate validation of the parallel or distributed model is required. A necessary first step for such a validation is an understanding of the sources of bias that might occur through parallelization or distribution of a simulation model. The intention of this paper is to give an overview of the various types of bias and to give a formal definition of the bias and its quantification. |
doi_str_mv | 10.1109/WSC.2005.1574273 |
format | Conference Proceeding |
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Therefore, validation and verification of simulation models is considered an indispensable method to establish the credibility of developed models. In the process of parallelizing or distributing a given credible simulation model, a bias is introduced, possibly leading to serious errors in simulation results. Depending on the mechanisms used for parallelization or distribution, a separate validation of the parallel or distributed model is required. A necessary first step for such a validation is an understanding of the sources of bias that might occur through parallelization or distribution of a simulation model. 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Therefore, validation and verification of simulation models is considered an indispensable method to establish the credibility of developed models. In the process of parallelizing or distributing a given credible simulation model, a bias is introduced, possibly leading to serious errors in simulation results. Depending on the mechanisms used for parallelization or distribution, a separate validation of the parallel or distributed model is required. A necessary first step for such a validation is an understanding of the sources of bias that might occur through parallelization or distribution of a simulation model. The intention of this paper is to give an overview of the various types of bias and to give a formal definition of the bias and its quantification.</abstract><pub>IEEE</pub><doi>10.1109/WSC.2005.1574273</doi></addata></record> |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Discrete event simulation Optimization methods |
title | Bias in parallel and distributed simulation systems |
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