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Computable Bounds on the Spectral Gap for Unreliable Jackson Networks

Part of: Special processes Markov processes

Published online by Cambridge University Press:  22 February 2016

Paweł Lorek  and
Ryszard Szekli
Paweł Lorek*
Affiliation:
University of Wrocław
Ryszard Szekli*
Affiliation:
University of Wrocław
*
∗ Postal address: Mathematical Institute, University of Wroclaw, pl. Grunwaldzki 2/4, 50-384 Wrocław, Poland.
∗ Postal address: Mathematical Institute, University of Wroclaw, pl. Grunwaldzki 2/4, 50-384 Wrocław, Poland.
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Abstract

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The goal of this paper is to identify exponential convergence rates and to find computable bounds for them for Markov processes representing unreliable Jackson networks. First, we use the bounds of Lawler and Sokal (1988) in order to show that, for unreliable Jackson networks, the spectral gap is strictly positive if and only if the spectral gaps for the corresponding coordinate birth and death processes are positive. Next, utilizing some results on birth and death processes, we find bounds on the spectral gap for network processes in terms of the hazard and equilibrium functions of the one-dimensional marginal distributions of the stationary distribution of the network. These distributions must be in this case strongly light-tailed, in the sense that their discrete hazard functions have to be separated from 0. We relate these hazard functions with the corresponding networks' service rate functions using the equilibrium rates of the stationary one-dimensional marginal distributions. We compare the obtained bounds on the spectral gap with some other known bounds.

Keywords

Unreliable Jackson networkspectral gapexponential ergodicityCheeger's constant

MSC classification

Primary: 60K25: Queueing theory
Secondary: 60J25: Continuous-time Markov processes on general state spaces
Type
Research Article
Information
Advances in Applied Probability , Volume 47 , Issue 2 , June 2015 , pp. 402 - 424
Copyright
© Applied Probability Trust 

Footnotes

The work of both authors was supported by NCN Research Grant DEC-2011/01/B/ST1/01305.

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