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rmftool - A library to Compute (Refined) Mean Field Approximation(s)

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Abstract

Mean field approximation is a powerful technique to study the performance of large stochastic systems represented as systems of interacting objects. Applications include load balancing models, epidemic spreading, cache replacement policies, or large-scale data centers, for which mean field approximation gives very accurate estimates of the transient or steady-state behaviors. In a series of recent papers [9, 7], a new and more accurate approximation, called the refined mean field approximation is presented. Yet, computing this new approximation can be cumbersome. The purpose of this paper is to present a tool, called rmf tool, that takes the description of a mean field model, and can numerically compute its mean field approximations and refinement.
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Dates and versions

hal-03485044 , version 1 (17-12-2021)

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  • HAL Id : hal-03485044 , version 1

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Sebastian Allmeier, Nicolas Gast. rmftool - A library to Compute (Refined) Mean Field Approximation(s). TOSME 2021, Nov 2021, Online conference, France. ⟨hal-03485044⟩
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