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Journal Articles Advances in Applied Probability Year : 2020

The Equilibrium States of Large Networks of Erlang Queues

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Abstract

The equilibrium properties of allocation algorithms for networks with a large number of nodes with finite capacity are investigated. Every node is receiving a flow of requests. When a request arrives at a saturated node, i.e. a node whose capacity is fully utilized, an allocation algorithm may attempt to re-allocate the request to a non-saturated node. For the algorithms considered, the re-allocation comes at a price: either an extra-capacity is required in the system, or the processing time of a re-allocated request is increased. The paper analyzes the properties of the equilibrium points of the asymptotic associated dynamical system when the number of nodes gets large. At this occasion the classical model of {\em Gibbens, Hunt and Kelly} (1990) in this domain is revisited. The absence of known Lyapunov functions for the corresponding dynamical system complicates significantly the analysis. Several techniques are used: Analytic and scaling methods to identify the equilibrium points. We identify the subset of parameters for which the limiting stochastic model of these networks has multiple equilibrium points. Probabilistic approaches are used to prove the stability of some of them. A criterion of exponential stability with the spectral gap of the associated linear operator of equilibrium points is also obtained.

Dates and versions

hal-01920171 , version 1 (13-11-2018)

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Davit Martirosyan, Philippe Robert. The Equilibrium States of Large Networks of Erlang Queues. Advances in Applied Probability, In press, 52 (2), ⟨10.1017/apr.2020⟩. ⟨hal-01920171⟩
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