Constructor Detail

Method Detail

• ab_amva

   final static Ret.pfqnAMVAMS ab_amva(Matrix serviceTimes, Matrix N, Matrix V, Matrix nservers, List<SchedStrategy> schedStrategies, Boolean fcfsSchmidt, String marginalProbMethod)

  Akyildiz-Bolch AMVA method for multi-server BCMP networks.

  An approximate MVA algorithm using the Akyildiz-Bolch linearizer technique for closed queueing networks with multi-server stations.

  Parameters:

  serviceTimes - Service time matrix (M x K)

  N - Population vector (1 x K)

  V - Visit ratio matrix (M x K)

  nservers - Number of servers at each station (M x 1)

  schedStrategies - Scheduling strategies for each station

  fcfsSchmidt - Whether to use Schmidt formula for FCFS stations

  marginalProbMethod - Method for marginal probability calculation ("ab" or "scat")

  Returns:

  pfqnAMVAMS result containing Q, U, R, C, X, and iteration count

• ab_linearizer

   final static Ret.pfqnAMVA ab_linearizer(Integer K, Integer M, Matrix population, Matrix nservers, List<SchedStrategy> type, Matrix v, Matrix s, Boolean fcfsSchmidt, String marginalProbMethod)

  Akyildiz-Bolch linearizer method for multi-server BCMP networks.

  Parameters:

  K - Number of classes

  M - Number of stations

  population - Population vector

  nservers - Number of servers at each station

  type - Scheduling discipline at each station

  v - Visit matrix

  s - Service time matrix

  fcfsSchmidt - Whether to use Schmidt formula for FCFS

  marginalProbMethod - Method for marginal probability ("ab" or "scat")

  Returns:

  pfqnAMVA result with performance measures

• pfqn_ab_core

   final static Ret.pfqnAMVA pfqn_ab_core(Integer K, Integer M, Matrix population, Matrix nservers, List<SchedStrategy> type, Matrix v, Matrix s, Integer maxiter, Array<Array<DoubleArray>> D, Matrix lIn, Boolean fcfsSchmidt, String marginalProbMethod)

  Akyildiz-Bolch core method for multi-server BCMP networks.

  Parameters:

  K - Number of classes

  M - Number of stations

  population - Population vector (1D matrix of size K)

  nservers - Number of servers at each station

  type - Scheduling discipline at each station

  v - Visit matrix

  s - Service time matrix

  maxiter - Maximum number of iterations

  D - Fractional changes matrix

  lIn - Initial queue length matrix

  fcfsSchmidt - Whether to use Schmidt formula for FCFS

  marginalProbMethod - Method for marginal probability

  Returns:

  pfqnAMVA result with performance measures

• findMarginalProbs

   final static Map<Integer, Double> findMarginalProbs(Double avgJobs, Integer numServers, Matrix population, Integer classIdx, String marginalProbMethod)

  Finds marginal probabilities using specified method.

  Parameters:

  avgJobs - Average number of jobs

  numServers - Number of servers

  population - Population vector

  classIdx - Class index

  marginalProbMethod - Method ("scat" or "ab")

  Returns:

  Map of job count to probability