Random Number Generation

Description

Distributions

The simulation library provides support for generating random variates from various continuous and discrete distributions: uniform, exponential, normal, truncated normal, gamma, beta, Erlang, Weibull, Bernoulli, binomial, geometric, Poisson, and more.

Generators come in two flavors: as plain functions (taking an RNG and the parameters of the distribution as arguments), and as classes that subclass cRandom and encapsulate both the RNG and the parameters of the distribution.

Random number generators

OMNeT++ provides several random number generators (streams) and several random number generator algorithms (default is cMersenneTwister). RNGs can be configured in omnetpp.ini. RNGs are made available via the cRNG interface, and the cModule::getRNG() method. All functions returning random variates, etc. internally call cModule::getRNG() and cRNG::intRand(), cRNG::doubleRand().

Note: The documentation of individual functions may refer to the following publications as [LawKelton] or [Banks]:

• [LawKelton] Simulation Modeling and Analysis, A.M. Law and W.D. Kelton, 3rd ed., McGraw Hill, 2000
• [Banks] Handbook of Simulation, J. Banks, Wiley, 1998

Collaboration diagram for Random Number Generation:

Modules
	Utility functions
	Utility functions.
	Continuous Distributions
	Random variate generators for continuous distributions.
	Discrete Distributions
	Random variate generators for discrete distributions.

Classes
class	cRandom
	Abstract interface for random variate generator classes. More...
class	cRNG
	Abstract interface for random number generator classes. More...