| NewInput.MCCN {queueing} | R Documentation | 
Define the inputs of a MultiClass Closed Network
Description
Define the inputs of a MultiClass Closed Network
Usage
NewInput.MCCN(
  classes, vNumber, vThink, nodes, vType, vVisit, vService, method=1, tol=0.01
)
Arguments
| classes | The number of classes | 
| vNumber | A vector with the number of customers of each class | 
| vThink | A vector with the think time of each class | 
| nodes | The number of nodes in the network | 
| vType | A vector with the type of node: "Q" for queueing nodes or "D" for delay nodes | 
| vVisit | A matrix[i, j]. The rows represents the different visit count for each class i to each node j | 
| vService | A matrix[i, j]. The rows represents the different service time for each class i in each node j | 
| method | If method is 0, the exact MVA algorith is used. If method is 1, the Bard-Schweitzer approximation algorithm is used | 
| tol | If the parameter method is 1, this is the tolerance parameter of the algorithm | 
Details
Define the inputs of a MultiClass Closed Network
References
[Lazowska84]  Edward D. Lazowska, John Zahorjan, G. Scott Graham, and Kenneth C. Sevcik (1984).
Quantitative System Performance: Computer System Analysis Using Queueing Network Models.
Prentice-Hall, Inc., Englewood Cliffs, New Jersey
See Also
Examples
## See example in pag 142 in reference [Lazowska84] for more details.
classes <- 2
vNumber <- c(1, 1)
vThink <- c(0, 0)
nodes <- 2
vType <- c("Q", "Q")
vVisit <- matrix(data=c(10, 9, 5, 4), nrow=2, ncol=2, byrow=TRUE)
vService <- matrix(data=c(1/10, 1/3, 2/5, 1), nrow=2, ncol=2, byrow=TRUE)
i_MCCN1 <- NewInput.MCCN(classes, vNumber, vThink, nodes, vType, vVisit, vService)