Package org.cloudbus.cloudsim.distributions

Class UniformDistr

java.lang.Object

org.cloudbus.cloudsim.distributions.ContinuousDistributionAbstract

org.cloudbus.cloudsim.distributions.UniformDistr

All Implemented Interfaces:

ContinuousDistribution

public class UniformDistr
extends ContinuousDistributionAbstract

A pseudo random number generator following the Uniform continuous distribution.

Since:

CloudSim Toolkit 1.0

Author:

Marcos Dias de Assuncao

Field Summary

Fields inherited from interface org.cloudbus.cloudsim.distributions.ContinuousDistribution

NULL

Constructor Summary

Constructors

Constructor	Description
UniformDistr()	Creates new uniform pseudo random number generator that generates values between [0 and 1[ using the current time as seed.
UniformDistr(double min, double max)	Creates new uniform pseudo random number generator that produces values between a min (inclusive) and max (exclusive).
UniformDistr(double min, double max, long seed)	Creates new uniform pseudo random number generator.
UniformDistr(long seed)	Creates new uniform pseudo random number generator that generates values between [0 and 1[ using a given seed.

Method Summary

Modifier and Type	Method	Description
boolean	isApplyAntitheticVariates()	Indicates if the pseudo random number generator (PRNG) has to apply the Antithetic Variates Technique in order to reduce variance of experiments using this PRNG.
double	sample()	Generate a new pseudo random number.
static double	sample(Random rd, double min, double max)	Generates a new pseudo random number based on the generator and values provided as parameters.
UniformDistr	setApplyAntitheticVariates(boolean applyAntitheticVariates)	Defines if the pseudo random number generator (PRNG) has to apply the Antithetic Variates Technique in order to reduce variance of experiments using this PRNG.

Methods inherited from class org.cloudbus.cloudsim.distributions.ContinuousDistributionAbstract

getSeed, setSeed

Methods inherited from class java.lang.Object

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

Constructor Detail

UniformDistr

public UniformDistr()

Creates new uniform pseudo random number generator that generates values between [0 and 1[ using the current time as seed.

UniformDistr

public UniformDistr(long seed)

Creates new uniform pseudo random number generator that generates values between [0 and 1[ using a given seed.

Parameters:

seed - simulation seed to be used

UniformDistr

public UniformDistr(double min,
                    double max)

Creates new uniform pseudo random number generator that produces values between a min (inclusive) and max (exclusive).

Parameters:

min - minimum value (inclusive)

max - maximum value (exclusive)

UniformDistr

public UniformDistr(double min,
                    double max,
                    long seed)

Creates new uniform pseudo random number generator.

Parameters:

min - minimum value (inclusive)

max - maximum value (exclusive)

seed - simulation seed to be used

Method Detail

sample

public double sample()

Description copied from interface: ContinuousDistribution

Generate a new pseudo random number.

Specified by:

sample in interface ContinuousDistribution

Overrides:

sample in class ContinuousDistributionAbstract

Returns:

the next pseudo random number in the sequence, following the implemented distribution.

sample

public static double sample(Random rd,
                            double min,
                            double max)

Generates a new pseudo random number based on the generator and values provided as parameters.

Parameters:

rd - the random number generator

min - the minimum value

max - the maximum value

Returns:

the next random number in the sequence

isApplyAntitheticVariates

public boolean isApplyAntitheticVariates()

Indicates if the pseudo random number generator (PRNG) has to apply the Antithetic Variates Technique in order to reduce variance of experiments using this PRNG. This technique doesn't work for all the cases. However, in the cases it can be applied, in order to it work, one have to perform some actions. Consider an experiment that has to run "n" times. The first half of these experiments has to use the seeds the developer want. However, the second half of the experiments have to set the applyAntitheticVariates attribute to true and use the seeds of the first half of experiments. Thus, the first half of experiments are run using PRNGs that return random numbers as U(0, 1)[seed_1], ..., U(0, 1)[seed_n]. The second half of experiments then uses the seeds of the first half of experiments, returning random numbers as 1 - U(0, 1)[seed_1], ..., 1 - U(0, 1)[seed_n].

Returns:

true if the technique has to be applied, false otherwise

setApplyAntitheticVariates

public UniformDistr setApplyAntitheticVariates(boolean applyAntitheticVariates)

Defines if the pseudo random number generator (PRNG) has to apply the Antithetic Variates Technique in order to reduce variance of experiments using this PRNG.

Parameters:

applyAntitheticVariates - true if the technique has to be applied, false otherwise

See Also:

isApplyAntitheticVariates()