CLONES: CLOsed queueing Networks Exact Sampling

  • CLONES is a Matlab toolbox to realize CLosed queueing Networks Exact Sampling. Clones refers to an eponymous paper presented at the conference ValueTools2014.
  • Developer : C. Rovetta
  • Last version : 2015-05-11
  • Download : V2.0
  • Paper : Clones.pdf
Classes
Model
Properties:
  • M: [1x1 int] number of customers
  • K: [1x1 int] number of queues
  • M: [1x1 int] number of customers
  • C: [1xK int] vector of capacity
  • E: [1xK int] vector of number of serveur in each queues
  • P: [KxK double] routing matrix
  • Mu: [1xK int] vector of service rate for each serveur in each queue
  • Nu: [1xK double] vector of service rate for each queue
  • Nuu: [1xK double] cumsum of Nu
  • PP: [KxK double] cumsum of P
Methods:
Model=Clones_Model('Example',C,E,Mu,P,M) Constructs the model Model
print(Model) Prints parameters of Model
X=PSS(Model,nb) Poduces nb sampler according the model with the PSS algorithm
X=PSD(Model,nb) Poduces nb sampler according the model with the PSD algorithm
X=PSF(Model,nb) Poduces nb sampler according the model with the PSF algorithm
States
Properties:
  • Mod: [1x1 Clones_Model] model to consider
  • K: [1x1 int] number of queues
  • M: [1x1 int] number of customers
  • C: [1xK int] vector of capacity
  • S: [L1xK int] states matrix
  • cS: [L2xK int] state space matrix
Methods:
States=Clones_S(Model) Constructs States from the Model, as the state space
c=card(States) Returns the number of states in S
print(States) Prints S
States=t(States,[i j]) Computes the transition tij(S)
States=t(States,[i j m]) Computes the transition tijm(S)
States=reset(States) Transphorms S into the state space (ie. S=cS)
Diagram
Properties:
  • Mod: [1x1 Clones_Model] model to consider
  • K: [1x1 int] number of queues
  • M: [1x1 int] number of customers
  • C: [1xK int] vector of capacity
  • D: [(M+1)xK(M+1) bool] diagram matrix
  • cD: [(M+1)xK(M+1) bool] complete diagram matrix
Methods:
Diagram=Clones_D(Model) Constructs Diagram from the Model, as the complete diagram
plot(Model,option) Plots the diagram corresponding to D
Diagram=T(Diagram,[i j]) Computes the transition Tij(D)
Diagram=Tm(Diagram,[i j m]) Computes the transition Tijm(D)
S=Psi(Diagram) Returns the matrix S=Psi(D)
cp=cardPsi(Diagram) Returns the number |Psi(D)|
test=onePath(Diagram) Tests if Diagram contains only one path
Diagram=reset(Diagram) Transphorms D into the complete diagram (ie. D=cD)
Gap-free diagram
Properties:
  • Mod: [1x1 Clones_Model] model to consider
  • K: [1x1 int] number of queues
  • M: [1x1 int] number of customers
  • C: [1xK int] vector of capacity
  • F: [2x(sum(C)+K) bool] gap-free diagram matrix
  • cF: [2x(sum(C)+K) bool] complete gap-free diagram matrix
Methods:
GapFree=Clones_F(Model) Constructs GapFree from the Model, as the complete diagram
plot(Model,option) Plots the diagram corresponding to F
GapFree=gfT(GapFree,[i j]) Computes the gap-free transition Tij(F)
GapFree=gfTm(GapFree,[i j m]) Computes the gap-free transition Tijm(F)
S=Psi(GapFree) Returns the matrix S=Psi(F)
cp=cardPsi(GapFree) Returns the number |Psi(F)|
test=onePath(GapFree) Tests if F contains only one path
GapFree=reset(GapFree) Transphorms F into a complete diagram (ie. F=cF)
Diagram=FtoG(GapFree) Transphorms GapFree into an object diagram