cdf_respt_distrib.m

clear node jobclass;
model = Network('model');
 
node{1} = Delay(model, 'Delay');
node{2} = Queue(model, 'Queue1', SchedStrategy.PS);
 
jobclass{1} = ClosedClass(model, 'Class1', 1, node{1}, 0);
node{1}.setService(jobclass{1}, Exp.fitMean(1.0));
node{2}.setService(jobclass{1}, Exp.fitMean(2.0));
 
jobclass{2} = ClosedClass(model, 'Class2', 3, node{1}, 0);
node{1}.setService(jobclass{2}, Erlang.fitMeanAndOrder(4.0,2));
node{2}.setService(jobclass{2}, HyperExp.fitMeanAndSCV(5.0,30.0));
 
P = cell(2);
P{1,1} = circul(2);
P{1,2} = zeros(2);
P{2,1} = zeros(2);
P{2,2} = circul(2);
 
% model
model.link(P);
RDfluid = FLD(model).getCdfRespT()
jmtoptions = JMT.defaultOptions; 
jmtoptions.samples = 1e5;
jmtoptions.seed = 23000;
RDsim = JMT(model, jmtoptions).getTranCdfRespT();
 
%%
figure;
for i=1:model.getNumberOfStations
    subplot(model.getNumberOfStations,2,2*(i-1)+1)
    semilogx(RDsim{i,1}(:,2),1-RDsim{i,1}(:,1),'r')
    hold on;
    semilogx(RDfluid{i,1}(:,2),1-RDfluid{i,1}(:,1),'--')
    legend('jmt-transient','fluid-steady','Location','Best');
    title(['Tail: Node ',num2str(i),', Class ',num2str(1),', ',node{i}.serviceProcess{1}.name, ' service']);
    
    subplot(model.getNumberOfStations,2,2*(i-1)+2)
    semilogx(RDsim{i,2}(:,2),1-RDsim{i,2}(:,1),'r')
    hold on;
    semilogx(RDfluid{i,2}(:,2),1-RDfluid{i,2}(:,1),'--')
    legend('jmt-transient','fluid-steady','Location','Best');
    title(['Tail: Node ',num2str(i),', Class ',num2str(2),', ',node{i}.serviceProcess{2}.name, ' service']);
end
 
%%
for i=1:model.getNumberOfStations
    for c=1:model.getNumberOfClasses
        AvgRespTfromCDFfluid(i,c) = diff(RDfluid{i,c}(:,1))'*RDfluid{i,c}(2:end,2);
        AvgRespTfromCDFsim(i,c) = diff(RDsim{i,c}(:,1))'*RDsim{i,c}(2:end,2);
    end
end