public static Instances getKnowledgeBase() {
if (knowledgeBase == null) {
try {
// load knowledgebase from file
CreateAppInsertIntoVm.knowledgeBase =
Action.loadKnowledge(Configuration.getInstance().getKBCreateAppInsertIntoVm());
// prediction is also performed therefore the classifier and the evaluator must be
// instantiated
if (!isOnlyLearning()) {
System.out.println("Classify data CreateAppInsertInto");
if (knowledgeBase.numInstances() > 0) {
classifier = new MultilayerPerceptron();
classifier.buildClassifier(knowledgeBase);
evaluation = new Evaluation(knowledgeBase);
evaluation.crossValidateModel(
classifier,
knowledgeBase,
10,
knowledgeBase.getRandomNumberGenerator(randomData.nextLong(1, 1000)));
System.out.println("Classified data CreateAppInsertInto");
} else {
System.out.println("No Instancedata for classifier CreateAppInsertIntoVm");
}
}
} catch (Exception e) {
e.printStackTrace();
}
}
return knowledgeBase;
}
@Override
public void init(Resource problemApp) {
this.setProblemResource(problemApp);
this.setProblemType(problemApp.getProblemType());
this.preconditionsOk = false;
this.curInstance = null;
this.selectedVm = null;
this.costs = 0;
this.app = null;
this.costs = Configuration.getInstance().getAppInsertIntoVmCosts();
if (problemApp instanceof App) { // only apps can be inserted
app = (App) problemApp;
if (app.getVm() == null) { // only new apps can be inserted
prediction = 0;
int curFitFactor = 0;
for (PhysicalMachine pm : Monitor.getInstance().getPms()) {
if (pm.isRunning()) {
for (VirtualMachine vm : pm.getVms()) {
curFitFactor = calculateFit(app, vm);
if (curFitFactor > prediction) {
preconditionsOk = true;
prediction = curFitFactor;
this.selectedVm = vm;
}
}
}
}
}
}
}
public void terminate() {
try {
Action.saveKnowledge(
Configuration.getInstance().getKBCreateAppInsertIntoVm(),
CreateAppInsertIntoVm.getKnowledgeBase());
} catch (IOException e) {
e.printStackTrace();
}
}