Heavy-traffic path-time distribution conjecture for roving server networks

Let Wi1,i2,,iMW_{i_1,i_2,\dots,i_M} be the path time along the customer route i1,i2,,iMi_1,i_2,\dots,i_M, and let Wi1,i2,,iMfluid\mathcal{W}^{\textit{fluid}}_{i_1,i_2,\dots,i_M} be the corresponding standardised path time in the fluid model. Let Γ\Gamma have a Gamma distribution with parameters α+1\alpha+1 and δμ\delta\mu. Path-time conjecture. As ρ1\rho\uparrow1, the scaled path time satisfies

(1ρ)Wi1,i2,,iMdΓ×Wi1,i2,,iMfluid.(1-\rho)W_{i_1,i_2,\dots,i_M}\xrightarrow{d}\Gamma\times\mathcal{W}^{\textit{fluid}}_{i_1,i_2,\dots,i_M}.

This applies for i,k=1,,Ni,k=1,\dots,N; the distribution of the fluid factor is given by the path-time fluid analysis. It extends the heavy-traffic snapshot principle from queue lengths and waiting times to routed customer paths, while the general result remains conjectural.

Sources & referencesView supporting material

Primary source

Marko Boon, Rob van der Mei and Erik Winands, “Heavy traffic analysis of roving server networks”, arXiv:1611.02608 (2016).

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