Networks of interacting stochastic fluid models with infinite and finite buffers

Nikki Sonenberg () and Peter G. Taylor
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Nikki Sonenberg: The University of Melbourne
Peter G. Taylor: The University of Melbourne

Queueing Systems: Theory and Applications, 2019, vol. 92, issue 3, No 4, 293-322

Abstract: Abstract Stochastic fluid models have been widely used to model the level of a resource that changes over time, where the rate of variation depends on the state of some continuous-time Markov process. Latouche and Taylor (Queueing Syst 63:109–129, 2009) introduced an approach, using matrix analytic methods and the reduced load approximation for loss networks, to analyse networks of fluid models all driven by the same modulating process where the buffers are infinite. We extend the method to networks involving finite buffer models and illustrate the approach by deriving performance measures for a simple network as characteristics such as buffer size are varied. Our results provide insight into the situations where the infinite buffer model is a reasonable approximation to the finite buffer model.

Keywords: Stochastic fluid models; Ad hoc networks; Matrix analytic methods; Finite buffers; 60J20; 90B15 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11134-019-09619-w

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