Mean field approximation is a powerful tool to study the performance of large stochastic systems that is known to be exact as the system’s size N goes to infinity. Recently, it has been shown that, when one wants to compute expected performance metric in steady-state, mean field approximation can be made more accurate by adding a term in 1/N to the original approximation. This is called the refined mean field approximation in . In this paper, we show how to obtain the same result for the transient regime and we provide a further refinement by expanding the term in 1/N 2 (both for transient and steady-state regime). Our derivations are inspired by moment-closure approximation. We provide a number of examples that show this new approximation is usable in practice for systems with up to a few tens of dimensions.
|Titolo:||Size expansions of mean field approximation: Transient and steady-state analysis|
|Data di pubblicazione:||2019|
|Appare nelle tipologie:||1.1 Articolo in rivista|