The heavy traffic limit of an unbalanced generalized processor sharing model

Ramanan, Kavita; Reiman, Martin I.

The heavy traffic limit of an unbalanced generalized processor sharing model

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Description

This work considers a server that processes $J$ classes using the generalized processor sharing discipline with base weight vector $α=(α_1,...,α_J)$ and redistribution weight vector $β=(β_1,...,β_J)$. The invariant manifold $\mathcal{M}$ of the so-called fluid limit associated with this model is shown to have the form $\mathcal{M}=\{x\in\mathbb{R}_+^J:x_j=0 for j\in\mathcal{S}\}$, where $\mathcal{S}$ is the set of strictly subcritical classes, which is identified explicitly in terms of the vectors $α$ and $β$ and the long-run average work arrival rates $γ_j$ of each class $j$. In addition, under general assumptions, it is shown that when the heavy traffic condition $\sum_{j=1}^Jγ_j=\sum_{j=1}^Jα_j$ holds, the functional central limit of the scaled unfinished work process is a reflected diffusion process that lies in $\mathcal{M}$. The reflected diffusion limit is characterized by the so-called extended Skorokhod map and may fail to be a semimartingale. This generalizes earlier results obtained for the simpler, balanced case where $γ_j=α_j$ for $j=1,...,J$, in which case $\mathcal{M}=\mathbb{R}_+^J$ and there is no state-space collapse. Standard techniques for obtaining diffusion approximations cannot be applied in the unbalanced case due to the particular structure of the GPS model. Along the way, this work also establishes a comparison principle for solutions to the extended Skorokhod map associated with this model, which may be of independent interest.
Published in at http://dx.doi.org/10.1214/07-AAP438 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)