ikr.simlib.distributions.continuous.statedep

## Class MMPPDistribution

• All Implemented Interfaces:
ReflectionConstructable, ReflectionConstructable3<SimNode,Parameters,RandomNumberGenerator>

public class MMPPDistribution
extends MAPDistribution
MMPP (Markov Modulated Poisson Process)
Meaning: Modeling of sources with multiple states e.g., at the call level State machine with $$m$$ states. Markovian process with the rate $$\lambda_i$$ in the state $$i$$ Markovian process for modulation with the transition rate $$q_{ij}$$ from state $$i$$ to state $$j$$ According to definition: $$q_{ii} = -\sum\limits_{i \neq i} = q_{ij}$$. Special case of the MAP with $$d_{ii} = \lambda_i$$, $$d_{ij} = 0 \forall (i \neq j)$$ and $$i_{ij} = q_{ij} - d_{ij}$$ number of states $$m$$ arrival rates $$\lambda_i$$ in the states transition rates $$q_{ij}$$ sojourn time $$S_i$$ in the state $$i$$ is negative exponentially distributed with the mean value $$E[S_i] = \frac{1}{\sum\limits_{i \neq i} q_{ij}} = \frac{-1}{q_{ii}}$$ sojourn probabilities $$P_i$$ from linear equation system $$\sum\limits_i q_{ji} \cdot P_j = 0 \forall i \mbox{ , } \sum\limits_i P_i = 1$$ average arrival rate: $$\lambda = \sum\limits_i P_i \cdot \lambda_i$$ -  [...].distribution = MMPPDistribution [...].distribution.States = 2 [...].distribution.EventRates = [0.1 0.9] [...].distribution.RMAP = [[-0.001 0.001] [0.001 -0.001]]  P. J. K�HN: Reminder on queueing theory for ATM networks. Telecommunication Systems, No. 5, 1996, pp. 1-24. G. D. STAMOULIS, M. E. ANAGNOSTOU, A. D. GEORGANTAS: Traffic source models for ATM networks: a survey. Computer Communications, Vol. 17, No. 6, Juni, 1994. H. HEFFES, D. M. LUCANTONI: A Markov modulated charcterization of packetized voice and data traffic and related statistical multiplexer performance. IEEE Journal on Selected Areas in Communications, Vol. SAC-4, No. 6, 1986, pp. 856-868.

• ### Nested classes/interfaces inherited from class ikr.simlib.distributions.continuous.statedep.MAPDistribution

MAPDistribution.MAPStateParameters

• ### Fields inherited from class ikr.simlib.distributions.continuous.statedep.MAPDistribution

noOfStates, stateParameters
• ### Fields inherited from class ikr.simlib.distributions.Distribution

rng
• ### Fields inherited from interface ikr.simlib.parameters.reflection.ReflectionConstructable

CREATE_INSTANCE_METHOD_NAME
• ### Constructor Summary

Constructors
Constructor and Description
MMPPDistribution(int noOfStates, double[] eventRates, double[][] transitionRates)
MMPPDistribution(int noOfStates, double[] eventRates, double[][] transitionRates, RandomNumberGenerator rng)
• ### Method Summary

Methods
Modifier and Type Method and Description
static MMPPDistribution createInstance(SimNode ownNode, Parameters pars, RandomNumberGenerator rng)
• ### Methods inherited from class ikr.simlib.distributions.continuous.statedep.MAPDistribution

getCurrentState, next, reset
• ### Methods inherited from class ikr.simlib.distributions.Distribution

getDefaultRNG, getRandomNumberGenerator
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### MMPPDistribution

public MMPPDistribution(int noOfStates,
double[] eventRates,
double[][] transitionRates,
RandomNumberGenerator rng)
• #### MMPPDistribution

public MMPPDistribution(int noOfStates,
double[] eventRates,
double[][] transitionRates)
• ### Method Detail

• #### createInstance

public static MMPPDistribution createInstance(SimNode ownNode,
Parameters pars,
RandomNumberGenerator rng)