Package jline.api.qsys
Class GeoXGeo1Result
java.lang.Object
jline.api.qsys.GeoXGeo1Result
Result of a discrete-time Geo^X/Geo/1 queue analysis.
All time quantities are in slots. Unlike the single-arrival Geo/Geo/1, the
stationary queue length has no elementary closed form for a general batch
law, so the distribution is exposed through its probability generating
function
rather than a pmf. The mean measures are exact.invalid reference
#pgf(double)
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Constructor Summary
ConstructorsConstructorDescriptionGeoXGeo1Result(GeoGeo1Convention convention, double batchArrivalProb, double batchMean, double batchSecondFactorialMoment, double serviceProb, double arrivalRate, double utilization, double emptyProb, double meanQueueLength, double meanWaitingQueue, double meanSojournTime, double meanWaitingTime, double meanServiceTime) -
Method Summary
Modifier and TypeMethodDescriptiondoubleJobs arriving per slot, a*E[X].doublePer-slot probability that a batch arrives.doubleMean batch size E[X], conditional on a batch arriving.doubleSecond factorial moment E[X(X-1)] of the batch size.doubleProbability that the system is empty AT THE SLOT BOUNDARY,1 - lambda/s.Observation epoch the metrics refer to.doubleMean number of jobs in the system.doubleMean service time in slots, 1/s under LAS_DA and (1-s)/s under EAS.doubleMean sojourn time in slots, per job (not per batch).doubleMean number of jobs waiting, i.e.doubleMean waiting time in slots, per job.doublePer-slot service completion probability s.doubleDepartures per slot, equal to the arrival rate in steady state.doubleFraction of slots in which the server is serving, lambda/s.doublepgf(double z, double batchPgfAtZ) Probability generating function of the stationary queue length at the observation epoch, evaluated by the caller-supplied batch pgf.toString()
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Constructor Details
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GeoXGeo1Result
public GeoXGeo1Result(GeoGeo1Convention convention, double batchArrivalProb, double batchMean, double batchSecondFactorialMoment, double serviceProb, double arrivalRate, double utilization, double emptyProb, double meanQueueLength, double meanWaitingQueue, double meanSojournTime, double meanWaitingTime, double meanServiceTime)
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Method Details
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getConvention
Observation epoch the metrics refer to. -
getBatchArrivalProb
public double getBatchArrivalProb()Per-slot probability that a batch arrives. -
getBatchMean
public double getBatchMean()Mean batch size E[X], conditional on a batch arriving. -
getBatchSecondFactorialMoment
public double getBatchSecondFactorialMoment()Second factorial moment E[X(X-1)] of the batch size. -
getServiceProb
public double getServiceProb()Per-slot service completion probability s. -
getArrivalRate
public double getArrivalRate()Jobs arriving per slot, a*E[X]. -
getThroughput
public double getThroughput()Departures per slot, equal to the arrival rate in steady state. -
getUtilization
public double getUtilization()Fraction of slots in which the server is serving, lambda/s. -
getBoundaryEmptyProb
public double getBoundaryEmptyProb()Probability that the system is empty AT THE SLOT BOUNDARY,1 - lambda/s.This is deliberately not epoch-dependent. It is the constant that appears in the generating function under both conventions. The empty probability at the EAS epoch is
p0 + s*pi_1, which has no elementary form for a general batch law; obtain it frompgf(double, double)in the limit if it is needed. -
getMeanQueueLength
public double getMeanQueueLength()Mean number of jobs in the system. -
getMeanWaitingQueue
public double getMeanWaitingQueue()Mean number of jobs waiting, i.e. not in service. -
getMeanSojournTime
public double getMeanSojournTime()Mean sojourn time in slots, per job (not per batch). -
getMeanWaitingTime
public double getMeanWaitingTime()Mean waiting time in slots, per job. -
getMeanServiceTime
public double getMeanServiceTime()Mean service time in slots, 1/s under LAS_DA and (1-s)/s under EAS. -
pgf
public double pgf(double z, double batchPgfAtZ) Probability generating function of the stationary queue length at the observation epoch, evaluated by the caller-supplied batch pgf.Under LAS_DA, with
A(z)the pgf of the number of jobs arriving in one slot andp0 = 1 - lambda/s,P(z) = p0 s (z-1) A(z) / ( z - A(z)(s + (1-s)z) )
Under EAS the epoch is one departure earlier, which divides out the departure step:P_EAS(z) = P(z) (s/z + 1 - s) + p0 s (1 - 1/z).- Parameters:
z- evaluation point,0 < z <= 1batchPgfAtZ- the slot-arrival pgfA(z)at the same z- Returns:
P(z)
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toString
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