Class ExperimentRunner<T extends Experiment<T>>

java.lang.Object
org.cloudsimplus.testbeds.AbstractRunnable
org.cloudsimplus.testbeds.ExperimentRunner<T>
Type Parameters:
T - the type of Experiment the runner will execute
All Implemented Interfaces:
Runnable
public abstract class ExperimentRunner<T extends Experiment<T>> extends AbstractRunnable
An abstract class to implement experiment runners. They run an experiment a given number of times and collect statistics about the execution. The runner represents a testbed compounded of a set of experiments that it runs.
Since:
CloudSim Plus 1.0
Author:
Manoel Campos da Silva Filho

  • Constructor Details

    • ExperimentRunner

      protected ExperimentRunner(long baseSeed, int simulationRuns)
      Creates an experiment runner with a given
      invalid reference 
      base seed
      that runs sequentially.
      Parameters:
      baseSeed - the seed to be used as base for each experiment seed
      simulationRuns - the number of times the experiment will be executed

    • ExperimentRunner

      protected ExperimentRunner(long baseSeed, int simulationRuns, boolean latexTableResultsGeneration, boolean parallel)

      Creates an experiment runner with a given

      invalid reference 
      base seed

      that runs sequentially.

      Parameters:
      baseSeed - the seed to be used as base for each experiment seed
      simulationRuns - the number of times the experiment will be executed
      latexTableResultsGeneration - Enables/disables the generation of a result table in LaTeX format for computed metrics.
      parallel - whether experiments will run in parallel or sequentially

    • ExperimentRunner

      protected ExperimentRunner(long baseSeed, int simulationRuns, boolean applyAntitheticVariates)

      Creates an experiment runner with a given

      invalid reference 
      base seed

      that runs sequentially.

      Parameters:
      baseSeed - the seed to be used as base for each experiment seed
      simulationRuns - the number of times the experiment will be executed
      applyAntitheticVariates - indicates if it's to be applied the Antithetic Variates Technique.

    • ExperimentRunner

      protected ExperimentRunner(long baseSeed, int simulationRuns, int batchesNumber, boolean applyAntitheticVariates)

      Creates an experiment runner with a given

      invalid reference 
      base seed

      that runs sequentially.

      Parameters:
      baseSeed - the seed to be used as base for each experiment seed
      simulationRuns - the number of times the experiment will be executed
      batchesNumber - number of simulation run batches (zero disables the batch means method)
      applyAntitheticVariates - indicates if it's to be applied the Antithetic Variates Technique.

    • ExperimentRunner

      protected ExperimentRunner(long baseSeed, int simulationRuns, int batchesNumber, boolean applyAntitheticVariates, boolean parallel, boolean latexTableResultsGeneration)

      Creates an experiment runner with a given

      invalid reference 
      base seed
      .
      Parameters:
      baseSeed - the seed to be used as base for each experiment seed
      simulationRuns - the number of times the experiment will be executed
      batchesNumber - number of simulation run batches (zero disables the batch means method)
      applyAntitheticVariates - indicates if it's to be applied the Antithetic Variates Technique.
      parallel - whether experiments will run in parallel or sequentially. It's just actually enabled when the simulationRuns is larger than 1.
      latexTableResultsGeneration - Enables/disables the generation of a result table in LaTeX format for computed metrics.

  • Method Details

    • batchSizeCeil

      public int batchSizeCeil()
      Returns:
      the batch size rounded by the Math.ceil(double) method.

    • isApplyBatchMeansMethod

      public boolean isApplyBatchMeansMethod()
      Checks if the "Batch Means Method" is to be applied to reduce correlation between the results for different experiment runs. That happens if the number of simulation runs and the number of batches are compatible.
      Returns:
      true if the "Batch Means Method" is to be applied, false otherwise.

    • computeBatchMeans

      protected List<Double> computeBatchMeans(List<Double> samples)
      Gets a list of samples and apply the "Batch Means Method" to reduce samples correlation, if the "Batch Means Method" is to be applied.
      Parameters:
      samples - the list with samples to apply the "Batch Means Method". Samples size is defined by the
      invalid reference 
      #getSimulationRuns()
      .
      Returns:
      the samples list after applying the "Batch Means Method", in case the method is enabled to be applied, which will reduce the array to the number of batches defined by
      invalid reference 
      #getBatchesNumber()
      (each value in the returned array will be the mean of every sample batch). Otherwise, returns the same given array

    • isSingleRun

      public boolean isSingleRun()
      Checks if the experiment will run a single time or not.
      Returns:
      true if the experiment will run a single time, false if there are multiple simulation runs.

    • getSeed

      public long getSeed(int experimentIndex)

    • createRandomGen

      public <S extends StatisticalDistribution> S createRandomGen(int experimentIndex, @NonNull @NonNull Function<Long,S> randomGenCreator)

      Uses the provided Function to create a pseudo random number generator (PRNG) for an experiment run. The given Function defines the kind and parameters for this PRNG internally. This method calls that Function just providing the seed to be used for the current experiment run.

      If it is to apply the

      invalid reference 
      Antithetic Variates Technique

      to reduce results variance, the second half of experiments will use the seeds from the first half.

      Parameters:
      experimentIndex - index of the experiment's run to create a PRNG
      randomGenCreator - a Function that receives a seed generated by the runner and returns a new instance of some PRNG
      Returns:
      the created PRNG with the seed provided by the runner
      See Also:

    • createRandomGen

      public ContinuousDistribution createRandomGen(int experimentIndex)
      Creates a pseudo random number generator (PRNG) for an experiment run that generates uniform values between [0..1[. If it is to apply the
      invalid reference 
      "Antithetic Variates Technique"
      to reduce results variance, the second half of experiments will use the seeds from the first half.
      Parameters:
      experimentIndex - index of the experiment's run to create a PRNG
      Returns:
      the created PRNG
      See Also:

    • createRandomGen

      public ContinuousDistribution createRandomGen(int experimentIndex, double minInclusive, double maxExclusive)

      Creates a pseudo random number generator (PRNG) for an experiment run that generates uniform values between [min .. max[. If it is to apply the

      invalid reference 
      "Antithetic Variates Technique"

      to reduce results' variance, the second half of experiments will use the seeds from the first half.

      Parameters:
      experimentIndex - index of the experiment's run to create a PRNG
      minInclusive - the minimum value the generator will return (inclusive)
      maxExclusive - the maximum value the generator will return (exclusive)
      Returns:
      the created PRNG
      See Also:

    • isToReuseSeedFromFirstHalfOfExperiments

      public boolean isToReuseSeedFromFirstHalfOfExperiments(int currentExperimentIndex)

    • halfSimulationRuns

      public int halfSimulationRuns()
      Returns:
      the half of
      invalid reference 
      #getSimulationRuns()

    • run

      public void run()
      Setups and starts the execution of all experiments sequentially or in parallel.

    • createExperimentInternal

      protected abstract T createExperimentInternal(int index)
      Creates an experiment to be run for the i'th time.
      Parameters:
      index - a number that identifies the experiment
      Returns:
      the created experiment
      See Also:
      • createExperiment(int)

    • computeFinalResults

      protected ConfidenceInterval computeFinalResults(Map.Entry<String, List<Double>> metricEntry)
      Computes final simulation results, including mean, standard deviations and confidence intervals for a given metric computed across all simulation runs.
      Parameters:
      metricEntry - a map entry represented by the name of the metric and its list of values across multiple simulation runs
      Returns:
      the computed ConfidenceInterval from the provided values for the metric

    • computeFinalStatistics

      protected final org.apache.commons.math3.stat.descriptive.SummaryStatistics computeFinalStatistics(List<Double> values)

      Creates a SummaryStatistics object from a list of Double values, allowing computation of statistics such as mean over these values. The method also checks if the

      invalid reference 
      Antithetic Variates

      and the Batch Means techniques are enabled, applying them over the given list of Doubles. These techniques are used for variance reduction.

      Parameters:
      values - the List of values to add to the SummaryStatistics object
      Returns:
      the SummaryStatistics object containing the double values, after applying the techniques for variance reduction.

    • addMetricValue

      protected final void addMetricValue(String metricName, Double value)

      Add a value to a given metric inside the metricsMap.

      This method must be called for each metric inside the experiment finish listener. The listener can be set inside the runner's createExperimentInternal(int).

      Parameters:
      metricName - the name of the metric to collect the data for a simulation run
      value - the value for at metric for a given simulation run. If null is given, that means no value was collected for that metric in the run, but the metric entry must exist in the metrics map, so that the final results' table shows the metric entry with 0.
      See Also:
      • invalid reference 
        Experiment#setAfterExperimentFinish(Consumer)

    • getMetricValues

      protected final List<Double> getMetricValues(String metricName)

    • computeAntitheticMeans

      protected List<Double> computeAntitheticMeans(List<Double> samples)

      Computes the antithetic means for the given samples if the

      invalid reference 
      "Antithetic Variates Technique" is to be applied
      .

      These values are the average between the first half of samples with the second half. By this way, the resulting value is an array with half the samples' length.

      NOTE: To correctly compute the antithetic values, the seeds from the first half of experiments must be used for the second half.

      Parameters:
      samples - the list of samples to compute the antithetic means from
      Returns:
      the computed antithetic means from the given samples if the "Antithetic Variates Technique" is to be applied, otherwise return the same given samples list.
      See Also:

    • printSimulationParameters

      protected abstract void printSimulationParameters()

    • setFirstExperimentCreated

      public void setFirstExperimentCreated(int firstExperimentCreated)

    • getFinishedRuns

      public int getFinishedRuns()