Package org.cloudsimplus.testbeds

Class ExperimentRunner<T extends Experiment>

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> extends AbstractRunnable
A base class to run a given experiment a defined 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 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 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 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 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 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 simulation runs 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:

    • computeBatchMeans

      protected List<Double> computeBatchMeans(List<Double> samples)
      Gets an 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 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 getBatchesNumber() (each value in the returned array will be the mean of every sample batch). Otherwise, returns the same given array

    • isApplyAntitheticVariates

      public final boolean isApplyAntitheticVariates()
      Checks if the "Antithetic Variates Technique" is to be applied to reduce results variance.
      Returns:
      See Also:

    • getSimulationRuns

      public final int getSimulationRuns()
      Gets the number of times the experiment will be executed in order to get values such as means and standard deviations. It has to be an even number if the "Antithetic Variates Technique" is to be used.
      Returns:

    • 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.

    • getBatchesNumber

      public int getBatchesNumber()
      Gets the number of batches in which the simulation runs will be divided. If this number is greater than 1, the "Batch Means Method" is used to reduce the correlation between experiment runs.
      Returns:

    • getBaseSeed

      public long getBaseSeed()
      Gets the seed to be used for the first executed experiment. The seed for each subsequent experiment is this seed plus the index of the experiment.
      Returns:

    • getSeed

      public long getSeed(int experimentIndex)

    • createRandomGen

      public <S extends StatisticalDistribution> S createRandomGen(int experimentIndex, Function<Long,S> randomGenCreator)
      Uses the provided Function to create a pseudo random number generator (PRNG) for a experiment run. The kind and parameters for this PRNG is defined internally by the given Function. This method calls that Function just providing the seed to be used for the current experiment run. If it is to apply the "Antithetic Variates Technique" to reduce results variance, the second half of experiments will used the seeds from the first half.
      Parameters:
      experimentIndex - index of the experiment 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 a experiment run that generates uniform values between [0 and 1[. If it is to apply the "Antithetic Variates Technique" to reduce results variance, the second half of experiments will used the seeds from the first half.
      Parameters:
      experimentIndex - index of the experiment 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 a experiment run that generates uniform values between [min and max[. If it is to apply the "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 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 getSimulationRuns()

    • getExperimentsExecutionTimeSecs

      public long getExperimentsExecutionTimeSecs()
      Time in seconds the experiments took to finish.
      Returns:

    • getExperimentsStartTimeSecs

      public long getExperimentsStartTimeSecs()
      Time in seconds the experiments started.
      Returns:

    • 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 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 show the metric entry with 0.
      See Also:

    • 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 "Antithetic Variates Technique" is to be applied. These values are the mean between the first half of samples with the second half. By this way, the resulting value is an array with half of 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)

    • getFirstExperimentCreated

      public int getFirstExperimentCreated()

    • setDescription

      public ExperimentRunner setDescription(String description)
      Sets a description for this experiment which is shown when it starts. It's also used to generate a caption for the Latex table.
      Parameters:
      description - the description to set
      See Also:

    • getDescription

      public String getDescription()

    • setResultsTableId

      public ExperimentRunner setResultsTableId(String resultsTableId)
      An id used to identify the experiment results table generated in formats such as Latex for computed metrics.
      Parameters:
      resultsTableId - the name to set
      See Also:
      • latexTableResultsGeneration

    • getResultsTableId

      public String getResultsTableId()

    • enableLatexTableResultsGeneration

      public ExperimentRunner enableLatexTableResultsGeneration()
      Enables the generation of a result table in Latex format for computed metrics.
      Returns:

    • isLatexTableResultsGeneration

      public boolean isLatexTableResultsGeneration()
      Checks if generation of a result table in Latex format for computed metrics is enabled.
      Returns:

    • isShowProgress

      public boolean isShowProgress()
      Checks if a progress bar is to be printed to show when each experiment run finishes. It's just printed when the number of simulations is greater than 1 and experiments are not set as verbose. It's shown by default if those conditions are met.
      Returns:

    • setShowProgress

      public ExperimentRunner<T> setShowProgress(boolean showProgress)
      Enable or disables a progress bar to show when each experiment run finishes. It's just printed when the number of simulations is greater than 1 and experiments are not set as verbose.
      Parameters:
      showProgress - true to enable the progress bar, false to disable
      Returns:

    • getFinishedRuns

      public int getFinishedRuns()

    • setProgressBarInNewLine

      public ExperimentRunner<T> setProgressBarInNewLine(boolean progressBarInNewLine)

    • isVerbose

      public boolean isVerbose()
      Checks if simulation results of the experiment have to be output. If parallel execution is enabled, you may consider disabling verbosity for individual Experiments created, since messages from different runs will be mixed up and may cause confusion.
      Overrides:
      isVerbose in class AbstractRunnable
      Returns:

    • isParallel

      public boolean isParallel()
      If experiments are executed in parallel, each experiment verbosity is disabled, otherwise, you'll see mixed log messages from different experiment runs.