Stochastic networks and measure-valued processes
Seminar Room 1, Newton Institute
AbstractMany stochastic networks with complex scheduling disciplines are hard to analyze using finite-dimensional state representations. In the context of two specific stochastic networks arising in applications, we show how measure-valued representations can be used to study stability properties as well as to obtain explicit expressions for performance measures in a suitable (mean-field or heavy traffic) asymptotic regime.
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