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N the previous chapter it has become clear that the evaluation of large closed queueing networks can be quite unattractive from a computational point of view; this was also the reason for addressing approximation schemes and bounding methods. In this chapter we go a different way to attack large queueing network models: hierarchical modelling and evaluation. We address a modelling and evaluation approach where large submodels are solved in isolation and where the results of such an isolated evaluation are used in other models. To be able to do so, however, we need load-dependent queueing stations, that is, queueing nodes in which the service rate depends on the number of customers present. In Section 12.1 we introduce load-dependent servers and show the corresponding productform results for closed queueing networks including such servers. We then continue with the extension of the convolution algorithm to include load-dependent service stations in Section 12.2 and discuss two important special cases, namely infinite-server systems and multi-server systems, in Section 12.3. In Section 12.4 we extend the mean-value analysis method to the load-dependent case. We then outline an exact hierarchical decomposition approach using load-dependent service centers in Section 12.5. The hierarchical decomposition method can also be used in an approximate fashion; an example of that is discussed in Section 12.6, where we study memory management issues in time-sharing computer systems. barcode in excel 2003 Barcode in Microsoft Excel 2007/ 2010 /2013/2016
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