We extend the convolution and mean value analysis algorithms to incorporate composite servers that result from the aggregation of stations in a multiple class queueing network model. The method defines a new composite server device factor that is used in the product form solution of the aggregated network. The approximate analysis of multiclass networks can then be handled in a computationally efficient manner provided that a sufficient condition is satisfied.
Computational Aspects of Aggregation in Multiple Class Queueing Networks
BALBO, Gianfranco;
1983-01-01
Abstract
We extend the convolution and mean value analysis algorithms to incorporate composite servers that result from the aggregation of stations in a multiple class queueing network model. The method defines a new composite server device factor that is used in the product form solution of the aggregated network. The approximate analysis of multiclass networks can then be handled in a computationally efficient manner provided that a sufficient condition is satisfied.
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