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

#include "random-variable-stream.h"

Inheritance diagram for ns3::LogNormalRandomVariable:

Collaboration diagram for ns3::LogNormalRandomVariable:

Public Member Functions
	LogNormalRandomVariable ()
	Creates a log-normal distribution RNG with the default values for mu and sigma. More...

uint32_t	GetInteger (uint32_t mu, uint32_t sigma)
	Returns a random unsigned integer from a log-normal distribution with the specified mu and sigma. More...

virtual uint32_t	GetInteger (void)
	Returns a random unsigned integer from a log-normal distribution with the current mu and sigma. More...

double	GetMu (void) const
	Returns the mu value for the log-normal distribution returned by this RNG stream. More...

double	GetSigma (void) const
	Returns the sigma value for the log-normal distribution returned by this RNG stream. More...

double	GetValue (double mu, double sigma)
	Returns a random double from a log-normal distribution with the specified mu and sigma. More...

virtual double	GetValue (void)
	Returns a random double from a log-normal distribution with the current mu and sigma. More...

Public Member Functions inherited from ns3::RandomVariableStream
	RandomVariableStream ()
	Default constructor. More...

virtual	~RandomVariableStream ()
	Destructor. More...

int64_t	GetStream (void) const
	Returns the stream number for the RngStream. More...

bool	IsAntithetic (void) const
	Check if antithetic values will be generated. More...

void	SetAntithetic (bool isAntithetic)
	Specify whether antithetic values should be generated. More...

void	SetStream (int64_t stream)
	Specifies the stream number for the RngStream. More...

Public Member Functions inherited from ns3::Object
	Object ()
	Constructor. More...

virtual	~Object ()
	Destructor. More...

void	AggregateObject (Ptr< Object > other)
	Aggregate two Objects together. More...

void	Dispose (void)
	Dispose of this Object. More...

AggregateIterator	GetAggregateIterator (void) const
	Get an iterator to the Objects aggregated to this one. More...

virtual TypeId	GetInstanceTypeId (void) const
	Get the most derived TypeId for this Object. More...

template<typename T >
Ptr< T >	GetObject (void) const
	Get a pointer to the requested aggregated Object. More...

template<typename T >
Ptr< T >	GetObject (TypeId tid) const
	Get a pointer to the requested aggregated Object by TypeId. More...

void	Initialize (void)
	Invoke DoInitialize on all Objects aggregated to this one. More...

bool	IsInitialized (void) const
	Check if the object has been initialized. More...

Public Member Functions inherited from ns3::SimpleRefCount< Object, ObjectBase, ObjectDeleter >
	SimpleRefCount ()
	Default constructor. More...

	SimpleRefCount (const SimpleRefCount &o)
	Copy constructor. More...

uint32_t	GetReferenceCount (void) const
	Get the reference count of the object. More...

SimpleRefCount &	operator= (const SimpleRefCount &o)
	Assignment operator. More...

void	Ref (void) const
	Increment the reference count. More...

void	Unref (void) const
	Decrement the reference count. More...

Public Member Functions inherited from ns3::ObjectBase
virtual	~ObjectBase ()
	Virtual destructor. More...

void	GetAttribute (std::string name, AttributeValue &value) const
	Get the value of an attribute, raising fatal errors if unsuccessful. More...

bool	GetAttributeFailSafe (std::string name, AttributeValue &value) const
	Get the value of an attribute without raising erros. More...

void	SetAttribute (std::string name, const AttributeValue &value)
	Set a single attribute, raising fatal errors if unsuccessful. More...

bool	SetAttributeFailSafe (std::string name, const AttributeValue &value)
	Set a single attribute without raising errors. More...

bool	TraceConnect (std::string name, std::string context, const CallbackBase &cb)
	Connect a TraceSource to a Callback with a context. More...

bool	TraceConnectWithoutContext (std::string name, const CallbackBase &cb)
	Connect a TraceSource to a Callback without a context. More...

bool	TraceDisconnect (std::string name, std::string context, const CallbackBase &cb)
	Disconnect from a TraceSource a Callback previously connected with a context. More...

bool	TraceDisconnectWithoutContext (std::string name, const CallbackBase &cb)
	Disconnect from a TraceSource a Callback previously connected without a context. More...

Static Public Member Functions
static TypeId	GetTypeId (void)
	Register this type. More...

Static Public Member Functions inherited from ns3::RandomVariableStream
static TypeId	GetTypeId (void)
	Register this type. More...

Static Public Member Functions inherited from ns3::Object
static TypeId	GetTypeId (void)
	Register this type. More...

Static Public Member Functions inherited from ns3::ObjectBase
static TypeId	GetTypeId (void)
	Get the type ID. More...

Private Attributes
double	m_mu
	The mu value for the log-normal distribution returned by this RNG stream. More...

double	m_sigma
	The sigma value for the log-normal distribution returned by this RNG stream. More...

Additional Inherited Members
Protected Member Functions inherited from ns3::RandomVariableStream
RngStream *	Peek (void) const
	Get the pointer to the underlying RngStream. More...

Protected Member Functions inherited from ns3::Object
	Object (const Object &o)
	Copy an Object. More...

virtual void	DoDispose (void)
	Destructor implementation. More...

virtual void	DoInitialize (void)
	Initialize() implementation. More...

virtual void	NotifyNewAggregate (void)
	Notify all Objects aggregated to this one of a new Object being aggregated. More...

Protected Member Functions inherited from ns3::ObjectBase
void	ConstructSelf (const AttributeConstructionList &attributes)
	Complete construction of ObjectBase; invoked by derived classes. More...

virtual void	NotifyConstructionCompleted (void)
	Notifier called once the ObjectBase is fully constructed. More...

Related Functions inherited from ns3::ObjectBase
static TypeId	GetObjectIid (void)
	Ensure the TypeId for ObjectBase gets fully configured to anchor the inheritance tree properly. More...

Detailed Description

The log-normal 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 log-normal distribution. It also supports the generation of single random numbers from various log-normal distributions.

LogNormalRandomVariable defines a random variable with a log-normal distribution. If one takes the natural logarithm of random variable following the log-normal distribution, the obtained values follow a normal distribution.

The probability density function is defined over the interval [0, $+\infty$ ) as: $\frac{1}{x\sigma\sqrt{2\pi}} e^{-\frac{(ln(x) - \mu)^2}{2\sigma^2}}$ where $mean = e^{\mu+\frac{\sigma^2}{2}}$ and $variance = (e^{\sigma^2}-1)e^{2\mu+\sigma^2}$

The $\mu$ and $\sigma$ parameters can be calculated instead if the mean and variance are known with the following equations: $\mu = ln(mean) - \frac{1}{2}ln\left(1+\frac{variance}{mean^2}\right)$ , and, $\sigma = \sqrt{ln\left(1+\frac{variance}{mean^2}\right)}$

Here is an example of how to use this class:

double mu = 5.0;
double sigma = 2.0;
Ptr<LogNormalRandomVariable> x = CreateObject<LogNormalRandomVariable> ();
x->SetAttribute ("Mu", DoubleValue (mu));
x->SetAttribute ("Sigma", DoubleValue (sigma));
// The expected value for the mean of the values returned by a
// log-normally distributed random variable is equal to 
//
//                             2
//                   mu + sigma  / 2
//     E[value]  =  e                 .
//
double value = x->GetValue ();

Config Paths

ns3::LogNormalRandomVariable is accessible through the following paths with Config::Set and Config::Connect:

"/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::SimpleNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::CsmaNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::RateErrorModel/RanVar/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstStart/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::PointToPointNetDevice/ReceiveErrorModel/$ns3::BurstErrorModel/BurstSize/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::WifiNetDevice/Channel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::WaveNetDevice/Channel/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/DeviceList/[i]/$ns3::WaveNetDevice/Channel/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/ApplicationList/[i]/$ns3::DhcpClient/Transactions/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OnTime/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/ApplicationList/[i]/$ns3::OnOffApplication/OffTime/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanVelocity/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanDirection/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::GaussMarkovMobilityModel/MeanPitch/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Speed/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomDirection2dMobilityModel/Pause/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Direction/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWalk2dMobilityModel/Speed/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Speed/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/Pause/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/X/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomRectanglePositionAllocator/Y/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/X/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Y/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomBoxPositionAllocator/Z/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Theta/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::MobilityModel/$ns3::RandomWaypointMobilityModel/PositionAllocator/$ns3::RandomDiscPositionAllocator/Rho/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::ArpL3Protocol/RequestJitter/$ns3::LogNormalRandomVariable"
"/NodeList/[i]/$ns3::Icmpv6L4Protocol/SolicitationJitter/$ns3::LogNormalRandomVariable"
"/ChannelList/[i]/$ns3::YansWifiChannel/PropagationLossModel/$ns3::RandomPropagationLossModel/Variable/$ns3::LogNormalRandomVariable"
"/ChannelList/[i]/$ns3::YansWifiChannel/PropagationDelayModel/$ns3::RandomPropagationDelayModel/Variable/$ns3::LogNormalRandomVariable"

Attributes

Mu: The mu value for the log-normal distribution 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
Sigma: The sigma value for the log-normal distribution 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

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 are defined for this type.
Size of this type is 72 bytes (on a 64-bit architecture).

Definition at line 1299 of file random-variable-stream.h.

Constructor & Destructor Documentation

ns3::LogNormalRandomVariable::LogNormalRandomVariable ( )

Creates a log-normal distribution RNG with the default values for mu and sigma.

Definition at line 802 of file random-variable-stream.cc.

References NS_LOG_FUNCTION.

Member Function Documentation

uint32_t ns3::LogNormalRandomVariable::GetInteger	(	uint32_t	mu,
		uint32_t	sigma
	)

Returns a random unsigned integer from a log-normal distribution with the specified mu and sigma.

Parameters

[in]	mu	Mu value for the log-normal distribution.
[in]	sigma	Sigma value for the log-normal distribution.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic value returned, $x'$ , is calculated as follows:

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Definition at line 883 of file random-variable-stream.cc.

References GetValue(), and NS_LOG_FUNCTION.

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uint32_t ns3::LogNormalRandomVariable::GetInteger ( void )

virtual

Returns a random unsigned integer from a log-normal distribution with the current mu and sigma.

Returns: A random unsigned integer value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic value returned, $x'$ , is calculated as follows:

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Implements ns3::RandomVariableStream.

Definition at line 896 of file random-variable-stream.cc.

References GetValue(), m_mu, m_sigma, and NS_LOG_FUNCTION.

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double ns3::LogNormalRandomVariable::GetMu ( void ) const

Returns the mu value for the log-normal distribution returned by this RNG stream.

Returns: The mu value for the log-normal distribution returned by this RNG stream.

Definition at line 810 of file random-variable-stream.cc.

References m_mu, and NS_LOG_FUNCTION.

double ns3::LogNormalRandomVariable::GetSigma ( void ) const

Returns the sigma value for the log-normal distribution returned by this RNG stream.

Returns: The sigma value for the log-normal distribution returned by this RNG stream.

Definition at line 816 of file random-variable-stream.cc.

References m_sigma, and NS_LOG_FUNCTION.

TypeId ns3::LogNormalRandomVariable::GetTypeId ( void )

static

Register this type.

Returns: The object TypeId.

Definition at line 785 of file random-variable-stream.cc.

References m_mu, m_sigma, ns3::MakeDoubleAccessor(), and ns3::TypeId::SetParent().

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double ns3::LogNormalRandomVariable::GetValue	(	double	mu,
		double	sigma
	)

Returns a random double from a log-normal distribution with the specified mu and sigma.

Parameters

[in]	mu	Mu value for the log-normal distribution.
[in]	sigma	Sigma value for the log-normal distribution.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic value returned, $x'$ , is calculated as follows:

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 1.

Definition at line 849 of file random-variable-stream.cc.

References ns3::RandomVariableStream::IsAntithetic(), ns3::normal, NS_LOG_FUNCTION, ns3::RandomVariableStream::Peek(), ns3::RngStream::RandU01(), and sample-rng-plot::x.

Referenced by RandomVariableStreamLogNormalTestCase::ChiSquaredTest(), RandomVariableStreamLogNormalAntitheticTestCase::ChiSquaredTest(), RandomVariableStreamLogNormalTestCase::DoRun(), and RandomVariableStreamLogNormalAntitheticTestCase::DoRun().

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double ns3::LogNormalRandomVariable::GetValue ( void )

virtual

Returns a random double from a log-normal distribution with the current mu and sigma.

Returns: A floating point random value.

Note that antithetic values are being generated if m_isAntithetic is equal to true. If $u1$ and $u2$ are uniform variables over [0,1], then the value that would be returned normally, $x$ , is calculated as follows:

$\begin{eqnarray*} v1 & = & -1 + 2 * u1 \\ v2 & = & -1 + 2 * u2 \\ r2 & = & v1 * v1 + v2 * v2 \\ normal & = & v1 * \sqrt{\frac{-2.0 * \log{r2}}{r2}} \\ x & = & \exp{sigma * normal + mu} . \end{eqnarray*}$

For the antithetic case, $(1 - u1$ ) and $(1 - u2$ ) are the distances that $u1$ and $u2$ would be from $1$ . The antithetic value returned, $x'$ , is calculated as follows:

$\begin{eqnarray*} v1' & = & -1 + 2 * (1 - u1) \\ v2' & = & -1 + 2 * (1 - u2) \\ r2' & = & v1' * v1' + v2' * v2' \\ normal' & = & v1' * \sqrt{\frac{-2.0 * \log{r2'}}{r2'}} \\ x' & = & \exp{sigma * normal' + mu} . \end{eqnarray*}$

which now involves the distances $u1$ and $u2$ are from 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 890 of file random-variable-stream.cc.

References m_mu, m_sigma, and NS_LOG_FUNCTION.

Referenced by GetInteger().

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