Abstract
The predictive ability of queueing network models can be greatly enhanced if these models include the effects of system characteristics such as high service time variability and simultaneous resource possession, which violate the assumptions required for their efficient exact solution. In this paper we present a new approximate solution technique for queueing networks that include Coxian servers to represent resources at which customers have high service time variability. Our approach is unique in several respects: it is based directly on the theory of near-complete decomposability, it is non-iterative (performance measures for the queueing network of interest are expressed as linear combinations of the performance measures of a set of separable queueing networks), and it is conceptually and computationally simple.
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