Package jline.solvers.ctmc

Class SolverCTMC

java.lang.Object
jline.solvers.Solver
jline.solvers.NetworkSolver
jline.solvers.ctmc.SolverCTMC
Direct Known Subclasses:
CTMC
public class SolverCTMC extends NetworkSolver
Solver for Continuous-Time Markov Chain (CTMC) analysis of queueing networks.

SolverCTMC implements exact numerical analysis of queueing networks by constructing and solving the underlying continuous-time Markov chain. This approach provides exact results for steady-state and transient behavior of networks that may not satisfy product-form assumptions.

Key CTMC solver capabilities:

  • Exact CTMC state space construction and solution
  • Steady-state probability computation
  • Transient analysis with time-dependent solutions
  • Joint and marginal state probability distributions
  • Cache network modeling with exact hit/miss probabilities
  • General service and arrival process support

The solver automatically constructs the infinitesimal generator matrix Q and solves the balance equations πQ = 0 for steady-state analysis, or the differential equation dπ/dt = πQ for transient analysis.

Since:
1.0
See Also:

  • Constructor Details

  • Method Details

    • defaultOptions

      public static SolverOptions defaultOptions()

    • listValidMethods

      public List<String> listValidMethods()

    • getFeatureSet

      public static FeatureSet getFeatureSet()

    • printInfGen

      public static void printInfGen(SolverCTMC.generatorResult infGen, SolverCTMC.StateSpace stateSpace)

    • printInfGen

      public static void printInfGen(Matrix Q, Matrix SS)

    • printEventFilt

      public static void printEventFilt(SolverCTMC.generatorResult infGen, SolverCTMC.StateSpace stateSpace)

    • printEventFilt

      public static void printEventFilt(MatrixCell eventFilt, Matrix SS)

    • getCdfRespT

      public Matrix getCdfRespT(Matrix R)
      Get the cumulative distribution function of response times using tagged job methodology
      Parameters:
      R - Response time matrix or percentile values
      Returns:
      Matrix containing CDF values

    • getCdfSysRespT

      public Matrix getCdfSysRespT()
      Get the cumulative distribution function of system response times
      Returns:
      Matrix containing system-wide CDF values

    • getGenerator

      public SolverCTMC.generatorResult getGenerator()

    • getGenerator

      public SolverCTMC.generatorResult getGenerator(SolverOptions options)

    • getMarkedCTMC

      public MarkedMarkovProcess getMarkedCTMC()
      Get the MarkedCTMC representation of the model
      Returns:
      MarkedCTMC with generator and event filters

    • getMarkedCTMC

      public MarkedMarkovProcess getMarkedCTMC(SolverOptions options)
      Get the MarkedCTMC representation of the model with specified options
      Parameters:
      options - solver options
      Returns:
      MarkedCTMC with generator and event filters

    • getInfGen

      public SolverCTMC.generatorResult getInfGen()

    • getInfGen

      public SolverCTMC.generatorResult getInfGen(SolverOptions options)

    • getProb

      public Ret.ProbabilityResult getProb(int node, Matrix state)
      Description copied from class: NetworkSolver
      Returns marginal state probabilities for a specific node and state. This is an abstract method that must be implemented by concrete solver subclasses.
      Overrides:
      getProb in class NetworkSolver
      Parameters:
      node - the node index for which to compute probabilities
      state - the state vector to query (optional, null for all states)
      Returns:
      result containing marginal state probabilities

    • getProb

      public Ret.ProbabilityResult getProb(StatefulNode node, Matrix state)

    • getProb

      public Ret.ProbabilityResult getProb(StatefulNode node)

    • getProbAggr

      public Ret.ProbabilityResult getProbAggr(int node, Matrix state_a)
      Description copied from class: NetworkSolver
      Probability of a SPECIFIC per-class job distribution at a station. Returns P(n1 jobs of class 1, n2 jobs of class 2, ...) for given state.

      Compare with NetworkSolver.getProbMarg(int, int, jline.util.matrix.Matrix): returns queue-length distribution for a single class, i.e., P(n jobs of class r) for n=0,1,...,N(r).

      Overrides:
      getProbAggr in class NetworkSolver
      Parameters:
      node - the node index for which to compute probabilities
      state_a - per-class job counts, e.g., [2,1] = 2 class-1, 1 class-2
      Returns:
      scalar probability in [0,1]

    • getProbAggr

      public Ret.ProbabilityResult getProbAggr(StatefulNode node, Matrix state_a)

    • getProbAggr

      public Ret.ProbabilityResult getProbAggr(StatefulNode node)

    • getProbAggr

      public Ret.ProbabilityResult getProbAggr(Node node, Matrix state_a)

    • getProbAggr

      public Ret.ProbabilityResult getProbAggr(Node node)

    • getProbSys

      public Ret.ProbabilityResult getProbSys()
      Description copied from class: NetworkSolver
      Returns joint state probabilities for the entire system. This is an abstract method that must be implemented by concrete solver subclasses.
      Overrides:
      getProbSys in class NetworkSolver
      Returns:
      result containing joint state probabilities

    • getProbSysAggr

      public Ret.ProbabilityResult getProbSysAggr()
      Description copied from class: NetworkSolver
      Returns aggregated joint state probabilities for the entire system. This is an abstract method that must be implemented by concrete solver subclasses.
      Overrides:
      getProbSysAggr in class NetworkSolver
      Returns:
      result containing aggregated joint state probabilities

    • getStateSpace

      public SolverCTMC.StateSpace getStateSpace()

    • getStateSpace

      public SolverCTMC.StateSpace getStateSpace(SolverOptions options)

    • getStateSpaceAggr

      public Matrix getStateSpaceAggr()

    • getStruct

      public NetworkStruct getStruct(SolverCTMC solverCTMC)

    • getTranProb

      public Ret.ProbabilityResult getTranProb(StatefulNode node)

    • getTranProbAggr

      public Ret.ProbabilityResult getTranProbAggr(StatefulNode node)

    • getTranProbSys

      public Ret.ProbabilityResult getTranProbSys()

    • getTranProbSysAggr

      public Ret.ProbabilityResult getTranProbSysAggr()

    • runAnalyzer

      public void runAnalyzer() throws IllegalAccessException, ParserConfigurationException, IOException
      Description copied from class: Solver
      Executes the solver algorithm to analyze the model. This abstract method must be implemented by concrete solver classes.
      Specified by:
      runAnalyzer in class Solver
      Throws:
      IllegalAccessException - if access to required resources is denied
      ParserConfigurationException - if XML parsing configuration fails
      IOException - if I/O operations fail

    • sample

      public SolverCTMC.SampleResult sample(StatefulNode node, int numEvents)

    • sampleSys

      public Ret.SampleResult sampleSys(int numEvents)
      Description copied from class: NetworkSolver
      Samples joint system state trajectories. This is an abstract method that must be implemented by concrete solver subclasses.
      Overrides:
      sampleSys in class NetworkSolver
      Parameters:
      numEvents - the number of events to sample
      Returns:
      result containing sampled joint system state trajectories

    • supports

      public boolean supports(Network model)
      Description copied from class: Solver
      Checks if this solver supports the given network model. Default implementation returns true; subclasses should override to provide specific feature validation.
      Overrides:
      supports in class Solver
      Parameters:
      model - the network model to check
      Returns:
      true if the model is supported, false otherwise

    • sampleAggr

      public SolverCTMC.SampleResult sampleAggr(StatefulNode node, int numEvents)

    • sampleSysAggr

      public Ret.SampleResult sampleSysAggr(int numEvents)
      Description copied from class: NetworkSolver
      Samples aggregated joint system state trajectories. This is an abstract method that must be implemented by concrete solver subclasses.
      Overrides:
      sampleSysAggr in class NetworkSolver
      Parameters:
      numEvents - the number of events to sample
      Returns:
      result containing sampled aggregated joint system state trajectories

    • getRewardResult

      public RewardResult getRewardResult()
      Get reward computation results via value iteration. Computes cumulative rewards for all defined reward functions using value iteration on the uniformized CTMC.
      Returns:
      RewardResult containing value functions and steady-state rewards
      Throws:
      IllegalStateException - if no rewards are defined on the model

    • getRewardValueFunction

      public Matrix getRewardValueFunction(String rewardName)
      Get the value function for a specific reward.
      Parameters:
      rewardName - The name of the reward
      Returns:
      Matrix of size [Tmax+1 x nStates] containing V^k(s) values
      Throws:
      IllegalArgumentException - if reward name not found

    • getRewardTimeVector

      public double[] getRewardTimeVector()
      Get the time vector for reward computation.
      Returns:
      Time vector scaled by uniformization rate

    • getAvgReward

      public Map<String,Double> getAvgReward()
      Get steady-state expected reward for all rewards.
      Returns:
      Map from reward name to expected reward value

    • getAvgReward

      public double getAvgReward(String rewardName)
      Get steady-state expected reward for a specific reward.
      Parameters:
      rewardName - The name of the reward
      Returns:
      Expected reward value in steady state
      Throws:
      IllegalArgumentException - if reward name not found

    • getRewardNames

      public List<String> getRewardNames()
      Get the list of defined reward names.
      Returns:
      List of reward names

    • clearRewardResult

      public void clearRewardResult()
      Clear cached reward results to force recomputation.

    • runRewardAnalyzer

      public RewardResult runRewardAnalyzer()
      Run the reward analyzer and cache results. Convenience wrapper calling solver_ctmc_reward and storing results.
      Returns:
      RewardResult containing value functions, time vector, names, and steady-state rewards

    • getReward

      public RewardResult getReward(String rewardName)
      Get reward value function and state space, with optional filtering by reward name. Alias matching MATLAB getReward() signature.
      Parameters:
      rewardName - Optional reward name to filter. If null, returns all rewards.
      Returns:
      RewardResult containing value functions, time vector, names, state space

    • getReward

      public RewardResult getReward()
      Get reward value function and state space for all rewards.
      Returns:
      RewardResult containing all rewards

    • getTranReward

      public Map<String,double[]> getTranReward(String rewardName)
      Get transient expected reward E[r(X(t))] over time. Computes transient expected rewards using: E[r(X(t))] = sum_s pi_t(s) * r(s) where pi_t is the transient probability distribution at time t. Requires a finite timespan set via SolverCTMC(model, options.timespan([0,T])).
      Parameters:
      rewardName - Optional reward name to filter. If null, returns all rewards.
      Returns:
      Map from reward name to double[] of expected reward values at each time point. Use getRewardTimeVector() or the result's time field to get the corresponding time points.

    • getTranReward

      public Map<String,double[]> getTranReward()
      Get transient expected reward for all rewards.
      Returns:
      Map from reward name to transient expected reward time series