Instability in Stochastic and Fluid Queueing Networks
David Gamarnik, John Hasenbein
Abstract
The fluid model has proven to be one of the most effective tools for the analysis of stochastic queueing networks, specifically for the analysis of stability. It is known that stability of a fluid model implies positive (Harris) recurrence (stability) of a corresponding stochastic queueing network, and weak stability implies rate stability of a corresponding stochastic network. These results have been established both for cases of specific scheduling policies and for the class of all work conserving policies. However, only partial converse results have been established and in certain cases converse statements do not hold. In this paper we close one of the existing gaps. For the case of networks with two stations we prove that if the fluid model is not weakly stable under the class of all work conserving policies, then a corresponding queueing network is not rate stable under the class of all work conserving policies. We establish the result by building a particular work conserving scheduling policy which makes the associated stochastic process transient. An important corollary of our result is that the condition ρ*≤ 1, which was proven in daivan97 to be the exact condition for global weak stability of the fluid model, is also the exact global rate stability condition for an associated queueing network. Here ρ* is a certain computable parameter of the network involving virtual station and push start conditions.
Create a lesson
Related papers
Almost sure exponential stability of multi-dimensional stochastic systems driven by a symmetric α-stable process
Xuekang Zhang, Hongjian Liu, Guangjun Shen
The Arc Threshold of the Two-Row Ising Torus: Exact Factorization, an Algebraic Critical Coupling, Uniformity in the Circumference, and the Rate of Convergence
Marco Mandap
Markovian Lifts and Multifactor Approximations for Weighted Sub-fractional Brownian Motion
J. H. Ramirez-Gonzalez, Edison Cuba
Rényi mixing bounds for kinetic samplers via L2 hypocoercivity
Jianfeng Lu, Yinchen Luo
Bayesian Filters via the Stochastic Category
Kenichi Bannai, Masahiro Kurisaki
Synchronization of Enriched Spin Glasses
Franziska Engler, Justin Ko