Package jline.solvers.mam

Class SolverMAM

  • All Implemented Interfaces:
    
public class SolverMAM
extends NetworkSolver

    Solver for Matrix Analytic Methods (MAM) applied to queueing networks.

    SolverMAM implements matrix-analytic techniques for analyzing queueing networks with Markovian arrival processes (MAP), phase-type service distributions, and other non-exponential characteristics that go beyond product-form assumptions.

    Key MAM solver capabilities:

    • Markovian Arrival Process (MAP) modeling
    • Phase-type (PH) service distribution analysis
    • Matrix-geometric solution methods
    • Quasi-Birth-Death (QBD) process analysis
    • Non-product-form queueing network solutions
    • Passage time distribution computation

    This solver is particularly useful for networks with correlated arrivals, general service times, and complex dependency structures that cannot be analyzed using traditional product-form methods.

    Since:

    1.0

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description

    • Enum Constant Summary

      Enum Constants 
      Enum Constant Description

    • Method Summary

      Modifier and Type Method Description
      static SolverOptions defaultOptions()
      static FeatureSet getFeatureSet() Returns the feature set supported by the MAM solver
      NetworkStruct getStruct()
      List<String> listValidMethods(Network model)
      List<String> listValidMethods()
      void runAnalyzer() Executes the solver algorithm to analyze the model.
      boolean supports(Network model) Checks if this solver supports the given network model.
      Ret.DistributionResult getCdfRespT(AvgHandle R) Returns cumulative distribution functions of response times at steady-state.
      Ret.DistributionResult getCdfRespT() Returns cumulative distribution functions of response times at steady-state.
      Ret.DistributionResult getCdfPassT(AvgHandle R) Returns cumulative distribution functions of passage times at steady-state.
      Ret.DistributionResult getCdfPassT() Returns cumulative distribution functions of passage times at steady-state.
      Ret.DistributionResult getTranCdfPassT(AvgHandle R) Returns cumulative distribution functions of passage times during transient analysis.
      Ret.DistributionResult getTranCdfPassT() Returns cumulative distribution functions of passage times during transient analysis.
      Ret.ProbabilityResult getProbMarg(int node, int jobclass, Matrix state_m) Get marginal queue-length probability distribution for a job class.
      Ret.ProbabilityResult getProbMarg(int node, int jobclass) Get marginal queue-length probability distribution for a job class (all states).
      List<FJPercentileResult> getPerctRespT(Array<double> percentiles) Get response time percentiles from Fork-Join analysis This method retrieves percentile values computed by the FJ_codes algorithm for Fork-Join queueing systems.
      List<FJPercentileResult> getPerctRespT() Get response time percentiles using default values [50, 90, 95, 99]

      • Methods inherited from class jline.solvers.NetworkSolver

        aCT, aCT, aCT, aCT, aCT, aCT, aNCT, aNCT, aNCT, aNCT, aNCT, aNCT, aNT, aNT, aNT, aNT, aNT, aNT, aST, aST, aST, aT, aT, aT, aT, aT, aT, avg, avg, avg, avgArvR, avgArvRChain, avgArvRHandles, avgChain, avgChainT, avgChainT, avgChainT, avgChainT, avgChainT, avgChainT, avgChainTable, avgChainTable, avgChainTable, avgChainTable, avgChainTable, avgChainTable, avgHandles, avgNode, avgNodeArvRChain, avgNodeChain, avgNodeChainT, avgNodeChainT, avgNodeChainT, avgNodeChainT, avgNodeChainT, avgNodeChainT, avgNodeChainTable, avgNodeChainTable, avgNodeChainTable, avgNodeChainTable, avgNodeChainTable, avgNodeChainTable, avgNodeQLenChain, avgNodeResidTChain, avgNodeRespTChain, avgNodeT, avgNodeT, avgNodeT, avgNodeT, avgNodeT, avgNodeT, avgNodeTable, avgNodeTable, avgNodeTable, avgNodeTable, avgNodeTable, avgNodeTable, avgNodeTputChain, avgNodeUtilChain, avgQLen, avgQLenChain, avgQLenHandles, avgResidT, avgResidTChain, avgResidTHandles, avgRespT, avgRespTChain, avgRespTHandles, avgSys, avgSysRespT, avgSysT, avgSysT, avgSysT, avgSysTable, avgSysTable, avgSysTable, avgSysTput, avgT, avgT, avgT, avgT, avgT, avgT, avgTable, avgTable, avgTable, avgTable, avgTable, avgTable, avgTput, avgTputChain, avgTputHandles, avgUtil, avgUtilChain, avgUtilHandles, avgWaitT, cdfPassT, cdfPassT, cdfRespT, cdfRespT, chainAvgT, chainAvgT, chainAvgT, chainAvgT, chainAvgT, chainAvgT, getAllSolvers, getAvg, getAvg, getAvg, getAvgArvR, getAvgArvRChain, getAvgArvRHandles, getAvgChain, getAvgChainTable, getAvgChainTable, getAvgChainTable, getAvgChainTable, getAvgChainTable, getAvgChainTable, getAvgHandles, getAvgNode, getAvgNodeArvRChain, getAvgNodeChain, getAvgNodeChainTable, getAvgNodeChainTable, getAvgNodeChainTable, getAvgNodeChainTable, getAvgNodeChainTable, getAvgNodeChainTable, getAvgNodeQLenChain, getAvgNodeResidTChain, getAvgNodeRespTChain, getAvgNodeTable, getAvgNodeTable, getAvgNodeTable, getAvgNodeTable, getAvgNodeTable, getAvgNodeTable, getAvgNodeTputChain, getAvgNodeUtilChain, getAvgQLen, getAvgQLenChain, getAvgQLenHandles, getAvgResidT, getAvgResidTChain, getAvgResidTHandles, getAvgRespT, getAvgRespTChain, getAvgRespTHandles, getAvgSys, getAvgSys, getAvgSys, getAvgSysRespT, getAvgSysTable, getAvgSysTable, getAvgSysTable, getAvgSysTput, getAvgT, getAvgT, getAvgT, getAvgT, getAvgT, getAvgT, getAvgTable, getAvgTable, getAvgTable, getAvgTable, getAvgTable, getAvgTable, getAvgTput, getAvgTputChain, getAvgTputHandles, getAvgUtil, getAvgUtilChain, getAvgUtilHandles, getAvgWaitT, getChainAvgT, getChainAvgT, getChainAvgT, getChainAvgT, getChainAvgT, getChainAvgT, getDeadlineTable, getModel, getNodeAvgT, getNodeAvgT, getNodeAvgT, getNodeAvgT, getNodeAvgT, getNodeAvgT, getNodeChainAvgT, getNodeChainAvgT, getNodeChainAvgT, getNodeChainAvgT, getNodeChainAvgT, getNodeChainAvgT, getProb, getProb, getProbAggr, getProbAggr, getProbNormConstAggr, getProbSys, getProbSysAggr, getSjrnT, getSjrnT, getStageT, getStageT, getStageTable, getStageTable, getSysAvgT, getSysAvgT, getSysAvgT, getTranAvg, getTranCdfRespT, getTranCdfRespT, getTranHandles, hasAvgResults, hasDistribResults, hasTranResults, initHandles, model, nodeAvgT, nodeAvgT, nodeAvgT, nodeAvgT, nodeAvgT, nodeAvgT, nodeChainAvgT, nodeChainAvgT, nodeChainAvgT, nodeChainAvgT, nodeChainAvgT, nodeChainAvgT, print, prob, prob, probAggr, probAggr, probMarg, probMarg, probNormConstAggr, probSys, probSysAggr, runAnalyzerChecks, sample, sampleAggr, sampleSys, sampleSysAggr, setAvgHandles, setAvgResults, setDistribResults, setLang, setModel, setTranAvgResults, setTranHandles, setTranProb, sjrnT, sjrnT, stageT, stageTable, sysAvgT, sysAvgT, sysAvgT, tranAvg, tranCdfPassT, tranCdfPassT, tranCdfRespT, tranCdfRespT, tranHandles

      • Methods inherited from class jline.solvers.Solver

        getName, getOptions, getResults, hasResults, isJavaAvailable, isValidOption, listValidOptions, parseOptions, parseOptions, reset, resetRandomGeneratorSeed, setChecks, setOptions

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Method Detail

      • getFeatureSet

         static FeatureSet getFeatureSet()

        Returns the feature set supported by the MAM solver

        Returns:

        - the feature set supported by the MAM solver

      • runAnalyzer

         void runAnalyzer()

        Executes the solver algorithm to analyze the model. This abstract method must be implemented by concrete solver classes.

      • supports

         boolean supports(Network model)

        Checks if this solver supports the given network model. Default implementation returns true; subclasses should override to provide specific feature validation.

        Parameters:
        model - the network model to check
        Returns:

        true if the model is supported, false otherwise

      • getCdfRespT

         Ret.DistributionResult getCdfRespT(AvgHandle R)

        Returns cumulative distribution functions of response times at steady-state. This method computes response time distributions using matrix-analytic methods.

        Parameters:
        R - response time handles (optional)
        Returns:

        result containing CDFs for response times

      • getCdfRespT

         Ret.DistributionResult getCdfRespT()

        Returns cumulative distribution functions of response times at steady-state. Uses default response time handles.

        Returns:

        result containing CDFs for response times

      • getCdfPassT

         Ret.DistributionResult getCdfPassT(AvgHandle R)

        Returns cumulative distribution functions of passage times at steady-state.

        Parameters:
        R - response time handles (optional)
        Returns:

        result containing CDFs for passage times

      • getCdfPassT

         Ret.DistributionResult getCdfPassT()

        Returns cumulative distribution functions of passage times at steady-state. Uses default response time handles.

        Returns:

        result containing CDFs for passage times

      • getTranCdfPassT

         Ret.DistributionResult getTranCdfPassT(AvgHandle R)

        Returns cumulative distribution functions of passage times during transient analysis.

        Parameters:
        R - response time handles (optional)
        Returns:

        result containing transient CDFs for passage times

      • getTranCdfPassT

         Ret.DistributionResult getTranCdfPassT()

        Returns cumulative distribution functions of passage times during transient analysis. Uses default response time handles.

        Returns:

        result containing transient CDFs for passage times

      • getProbMarg

         Ret.ProbabilityResult getProbMarg(int node, int jobclass, Matrix state_m)

        Get marginal queue-length probability distribution for a job class.

        Computes the probability distribution P(n jobs of class r) for n=0,1,...,N(r) using MMAPPH1FCFS from BUTools.

        Current limitations:

        • Only supported for single queue models
        • Requires Queue station with FCFS scheduling
        Parameters:
        node - Station/node index (0-based)
        jobclass - Job class index (0-based)
        state_m - Optional state levels to query (null for all states, 0-based indexing)
        Returns:

        Probability result containing marginal probabilities

      • getProbMarg

         Ret.ProbabilityResult getProbMarg(int node, int jobclass)

        Get marginal queue-length probability distribution for a job class (all states).

        NOT YET IMPLEMENTED - This method is a stub.

        Parameters:
        node - Station/node index (0-based)
        jobclass - Job class index (0-based)
        Returns:

        Probability result - currently throws UnsupportedOperationException

      • getPerctRespT

         List<FJPercentileResult> getPerctRespT(Array<double> percentiles)

        Get response time percentiles from Fork-Join analysis

        This method retrieves percentile values computed by the FJ_codes algorithm for Fork-Join queueing systems. It automatically detects FJ topology and computes percentiles using the algorithm from "Beyond the Mean in Fork-Join Queues" (IFIP Performance 2015).

        Requirements:

        • Model must have valid Fork-Join topology: Source → Fork → K Queues → Join → Sink
        • Solver must have been run first (runAnalyzer() called)
        • Homogeneous service distributions across parallel queues
        Parameters:
        percentiles - Array of percentile levels (0-100 scale, e.g.
        Returns:

        List of FJPercentileResult, one per job class, containing: - jobClass: class index - percentiles: requested percentile levels - values: computed percentile values - K: number of parallel queues - method: algorithm used (e.g., "FJ_NARE")

      • getPerctRespT

         List<FJPercentileResult> getPerctRespT()

        Get response time percentiles using default values [50, 90, 95, 99]

        Returns:

        List of FJPercentileResult for default percentiles