The exponential distribution Random Number Generator (RNG) that allows stream numbers to be set deterministically. More...

#include <random-variable-stream.h>

Inheritance diagram for ns3::ExponentialRandomVariable:

Collaboration diagram for ns3::ExponentialRandomVariable:

Public Member Functions
	ExponentialRandomVariable ()
	Creates a exponential distribution RNG with the default values for the mean and upper bound.
double	GetBound (void) const
	Returns the upper bound on values that can be returned by this RNG stream.
uint32_t	GetInteger (uint32_t mean, uint32_t bound)
	Returns a random unsigned integer from an exponential distribution with the specified mean and upper bound.
virtual uint32_t	GetInteger (void)
	Returns a random unsigned integer from an exponential distribution with the current mean and upper bound.
double	GetMean (void) const
	Returns the mean value of the random variables returned by this RNG stream.
double	GetValue (double mean, double bound)
	Returns a random double from an exponential distribution with the specified mean and upper bound.
virtual double	GetValue (void)
	Returns a random double from an exponential distribution with the current mean and upper bound.
Public Member Functions inherited from ns3::RandomVariableStream
	RandomVariableStream ()
virtual	~RandomVariableStream ()
int64_t	GetStream (void) const
	Returns the stream number for this RNG stream.
bool	IsAntithetic (void) const
	Returns true if antithetic values should be generated.
void	SetAntithetic (bool isAntithetic)
	Specifies whether antithetic values should be generated.
void	SetStream (int64_t stream)
	Specifies the stream number for this RNG stream.
Public Member Functions inherited from ns3::Object
	Object ()
virtual	~Object ()
void	AggregateObject (Ptr< Object > other)
void	Dispose (void)
AggregateIterator	GetAggregateIterator (void) const
virtual TypeId	GetInstanceTypeId (void) const
template<typename T >
Ptr< T >	GetObject (void) const
template<typename T >
Ptr< T >	GetObject (TypeId tid) const
void	Start (void)
Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
	SimpleRefCount ()
	SimpleRefCount (const SimpleRefCount &o)
uint32_t	GetReferenceCount (void) const
SimpleRefCount &	operator= (const SimpleRefCount &o)
void	Ref (void) const
void	Unref (void) const
Public Member Functions inherited from ns3::ObjectBase
virtual	~ObjectBase ()
void	GetAttribute (std::string name, AttributeValue &value) const
bool	GetAttributeFailSafe (std::string name, AttributeValue &attribute) const
void	SetAttribute (std::string name, const AttributeValue &value)
bool	SetAttributeFailSafe (std::string name, const AttributeValue &value)
bool	TraceConnect (std::string name, std::string context, const CallbackBase &cb)
bool	TraceConnectWithoutContext (std::string name, const CallbackBase &cb)
bool	TraceDisconnect (std::string name, std::string context, const CallbackBase &cb)
bool	TraceDisconnectWithoutContext (std::string name, const CallbackBase &cb)

Static Public Member Functions
static TypeId	GetTypeId (void)
	This method returns the TypeId associated to ns3::ExponentialRandomVariable.

Private Attributes
double	m_bound
	The upper bound on values that can be returned by this RNG stream.
double	m_mean
	The mean value of the random variables returned by this RNG stream.

Additional Inherited Members
Protected Member Functions inherited from ns3::RandomVariableStream
RngStream *	Peek (void) const
	Returns a pointer to the underlying RNG stream.

Detailed Description

The exponential distribution Random Number Generator (RNG) that allows stream numbers to be set deterministically.

This class supports the creation of objects that return random numbers from a fixed exponential distribution. It also supports the generation of single random numbers from various exponential distributions.

The probability density function of an exponential variable is defined over the interval [0, $+\infty$ ) as: $\alpha e^{-\alpha x}$ where $\alpha = \frac{1}{mean}$

Since exponential distributions can theoretically return unbounded values, it is sometimes useful to specify a fixed upper limit. The bounded version is defined over the interval [0,b] as: $\alpha e^{-\alpha x} \quad x \in [0,b]$ . Note that in this case the true mean of the distribution is slightly smaller than the mean value specified: $1/\alpha - b/(e^{\alpha \, b}-1)$ .

Here is an example of how to use this class:

double mean = 3.14;
double bound = 0.0;
Ptr<ExponentialRandomVariable> x = CreateObject<ExponentialRandomVariable> ();
x->SetAttribute ("Mean", DoubleValue (mean));
x->SetAttribute ("Bound", DoubleValue (bound));
// The expected value for the mean of the values returned by an
// exponentially distributed random variable is equal to mean.
double value = x->GetValue ();

Definition at line 440 of file random-variable-stream.h.

Constructor & Destructor Documentation

ns3::ExponentialRandomVariable::ExponentialRandomVariable ( )

Creates a exponential distribution RNG with the default values for the mean and upper bound.

Definition at line 348 of file random-variable-stream.cc.

Member Function Documentation

double ns3::ExponentialRandomVariable::GetBound ( void ) const

Returns the upper bound on values that can be returned by this RNG stream.

Returns: The upper bound on values that can be returned by this RNG stream.

Definition at line 359 of file random-variable-stream.cc.

References m_bound.

uint32_t ns3::ExponentialRandomVariable::GetInteger	(	uint32_t	mean,
		uint32_t	bound
	)

Returns a random unsigned integer from an exponential distribution with the specified mean and upper bound.

Parameters

mean	Mean value of the random variables.
bound	Upper bound on values returned.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and

$x = - mean * \log(u)$

is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , is calculated as

$x' = - mean * \log(1 - u),$

which now involves the log of the distance $u$ is from the 1.

Definition at line 387 of file random-variable-stream.cc.

References GetValue().

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uint32_t ns3::ExponentialRandomVariable::GetInteger ( void )

virtual

Returns a random unsigned integer from an exponential distribution with the current mean and upper bound.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and

$x = - mean * \log(u)$

is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , is calculated as

$x' = - mean * \log(1 - u),$

which now involves the log of the distance $u$ is from the 1.

Implements ns3::RandomVariableStream.

Definition at line 398 of file random-variable-stream.cc.

References GetValue(), m_bound, and m_mean.

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double ns3::ExponentialRandomVariable::GetMean ( void ) const

Returns the mean value of the random variables returned by this RNG stream.

Returns: The mean value of the random variables returned by this RNG stream.

Definition at line 354 of file random-variable-stream.cc.

References m_mean.

TypeId ns3::ExponentialRandomVariable::GetTypeId ( void )

static

This method returns the TypeId associated to ns3::ExponentialRandomVariable.

This object is accessible through the following paths with Config::Set and Config::Connect:

/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanDirection/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanPitch/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanVelocity/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Pause/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Speed/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Direction/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Speed/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Pause/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/X/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Y/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Z/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Rho/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Theta/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/X/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/Y/$ns3::ExponentialRandomVariable
/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Speed/$ns3::ExponentialRandomVariable
/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OffTime/$ns3::ExponentialRandomVariable
/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OnTime/$ns3::ExponentialRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::ExponentialRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::ExponentialRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::ExponentialRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::ExponentialRandomVariable
/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::ExponentialRandomVariable

Attributes defined for this type:

Mean: The mean of the values returned by this RNG stream.
- Set with class: ns3::DoubleValue
- Underlying type: double -1.79769e+308:1.79769e+308
- Initial value: 1
- Flags: construct write read
Bound: The upper bound on the values returned by this RNG stream.
- Set with class: ns3::DoubleValue
- Underlying type: double -1.79769e+308:1.79769e+308
- Initial value: 0
- Flags: construct write read

Attributes defined in parent class ns3::RandomVariableStream:

Stream: The stream number for this RNG stream. -1 means "allocate a stream automatically". Note that if -1 is set, Get will return -1 so that it is not possible to know which value was automatically allocated.
- Set with class: ns3::IntegerValue
- Underlying type: int64_t -9223372036854775808:9223372036854775807
- Initial value: -1
- Flags: construct write read
Antithetic: Set this RNG stream to generate antithetic values
- Set with class: BooleanValue
- Underlying type: bool
- Initial value: false
- Flags: construct write read

No TraceSources defined for this type.

Reimplemented from ns3::RandomVariableStream.

Definition at line 332 of file random-variable-stream.cc.

References m_bound, m_mean, and ns3::TypeId::SetParent().

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double ns3::ExponentialRandomVariable::GetValue	(	double	mean,
		double	bound
	)

Returns a random double from an exponential distribution with the specified mean and upper bound.

Parameters

mean	Mean value of the random variables.
bound	Upper bound on values returned.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and

$x = - mean * \log(u)$

is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , is calculated as

$x' = - mean * \log(1 - u),$

which now involves the log of the distance $u$ is from the 1.

Definition at line 365 of file random-variable-stream.cc.

References ns3::RandomVariableStream::IsAntithetic(), ns3::RandomVariableStream::Peek(), and ns3::RngStream::RandU01().

Referenced by ns3::UanMacRc::Associate(), ns3::UanMacRc::AssociateTimeout(), RandomVariableStreamExponentialTestCase::ChiSquaredTest(), RandomVariableStreamExponentialAntitheticTestCase::ChiSquaredTest(), RandomVariableStreamExponentialTestCase::DoRun(), RandomVariableStreamExponentialAntitheticTestCase::DoRun(), ns3::UanMacRc::RtsTimeout(), ns3::UanMacRc::ScheduleData(), and ns3::UanMacRc::SendRts().

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double ns3::ExponentialRandomVariable::GetValue ( void )

virtual

Returns a random double from an exponential distribution with the current mean and upper bound.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u$ is a uniform variable over [0,1] and

$x = - mean * \log(u)$

is a value that would be returned normally, then $(1 - u$ ) is the distance that $u$ would be from $1$ . The value returned in the antithetic case, $x'$ , is calculated as

$x' = - mean * \log(1 - u),$

which now involves the log of the distance $u$ is from the 1.

Note that we have to re-implement this method here because the method is overloaded above for the two-argument variant and the c++ name resolution rules don't work well with overloads split between parent and child classes.

Implements ns3::RandomVariableStream.

Definition at line 393 of file random-variable-stream.cc.

References m_bound, and m_mean.

Referenced by GetInteger().

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