Minimal and Locally Edge Minimal Fluid Models for Resource-Sharing Networks

Author(s):  
Łukasz Kruk

We investigate minimal and locally edge minimal fluid models for real-time resource-sharing networks, which are natural counterparts of pathwise minimal and locally edge minimal performance processes for the corresponding real-time stochastic systems. The models under study arise as optimizers of appropriate idleness-based criteria within a suitable family of fluid models for a given resource-sharing network. The class of minimal fluid models is fairly general, corresponding to efficient service protocols in which transmission on each route takes place in the earliest deadline first (EDF) order. For such a model, the distribution of the current lead times of the fluid mass on each route coincides with the fluid arrival measure for this route, truncated below on the current frontier level. Locally edge minimal fluid models may be regarded, in some sense, as fluid counterparts of EDF resource-sharing networks. Under mild assumptions, a locally edge minimal fluid model is uniquely determined by its data. We also show stability of such models in the strictly subcritical case. More generally, each such a subcritical model converges to the invariant manifold in finite time.

2020 ◽  
Vol 92 (1) ◽  
pp. 33-76
Author(s):  
Łukasz Kruk

Abstract Motivated by an application to resource sharing network modelling, we consider a problem of greedy maximization (i.e., maximization of the consecutive minima) of a vector in $${\mathbb {R}}^n$$ R n , with the admissible set indexed by the time parameter. The structure of the constraints depends on the underlying network topology. We investigate continuity and monotonicity of the resulting maximizers with respect to time. Our results have important consequences for fluid models of the corresponding networks which are optimal, in the appropriate sense, with respect to handling real-time transmission requests.


Author(s):  
B W Weston ◽  
Z N Swingen ◽  
S Gramann ◽  
D Pojar

Abstract Background To describe the Strategic Allocation of Fundamental Epidemic Resources (SAFER) model as a method to inform equitable community distribution of critical resources and testing infrastructure. Methods The SAFER model incorporates a four-quadrant design to categorize a given community based on two scales: testing rate and positivity rate. Three models for stratifying testing rates and positivity rates were applied to census tracts in Milwaukee County, Wisconsin: using median values (MVs), cluster-based classification and goal-oriented values (GVs). Results Each of the three approaches had its strengths. MV stratification divided the categories most evenly across geography, aiding in assessing resource distribution in a fixed resource and testing capacity environment. The cluster-based stratification resulted in a less broad distribution but likely provides a truer distribution of communities. The GVs grouping displayed the least variation across communities, yet best highlighted our areas of need. Conclusions The SAFER model allowed the distribution of census tracts into categories to aid in informing resource and testing allocation. The MV stratification was found to be of most utility in our community for near real time resource allocation based on even distribution of census tracts. The GVs approach was found to better demonstrate areas of need.


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