Uses of Class
solvers.dataStructures.QNModel

Packages that use QNModel
Package
Description
Solution algorithms of JMVA.
Basis representations of the MoM and CoMoM exact solution algorithms of JMVA.
Control logic of the JMVA solvers.
Data structures shared by the JMVA solvers (tuples, positions, lists and matrices).
Linear system formulation shared by the MoM and CoMoM exact algorithms of JMVA.
Block Triangular Form (BTF) of the linear systems arising in the MoM and CoMoM algorithms, as described in the method of moments literature.
Macro blocks of the Block Triangular Form linear system decomposition used by the JMVA MoM and CoMoM solvers.
Micro blocks of the Block Triangular Form linear system decomposition used by the JMVA MoM and CoMoM solvers.
Top level blocks of the Block Triangular Form linear system decomposition used by the JMVA MoM and CoMoM solvers.
Simple linear system solvers used by JMVA.
Multiclass solution algorithms of JMVA: exact MVA, RECAL, MoM, CoMoM, TreeMVA and TreeConvolution for closed multiclass models, together with their approximate variants.
Queueing network model of JMVA: stations, classes, service demands and visits used by the exact and approximate solution algorithms.
Monte Carlo logistic regression used by the exact JMVA algorithms when the model dimension grows (logistic approximation of normalizing constants).
Monte Carlo logistic solvers of JMVA.
Tree based exact algorithms of JMVA: TreeMVA and TreeConvolution, which reduce the complexity of the exact solution of large closed models.
TreeMVA algorithm of JMVA, the tree based version of the exact Mean Value Analysis.
TreeConvolution algorithm of JMVA, the tree based version of the convolution algorithm.
Utilities of the JMVA solvers, such as the processing capacity checker used to verify that the workload can be processed by the network.