int main(void) {
char logFileName[300] = "/home/danconde/coleta/europa.log";
ResourceData parameters(0.5f, 100000);
bool answer;
DataCollector *dtCollector = new DataCollector(logFileName);
unsigned int i, count;
UsageData *testUsageData;
setValidResourceDataThreshold(0.9f);
setPredictionHours(6);
cout << "timestamp\tp_cpu\tp_mem\tanswer\tpcs\tvcs\tcoff" << endl;
// pcs = predicted cpu satisfability
// vcs = verified cpu satisfability
UsagePredictor *up = new UsagePredictor(new KMeansClusteringAlgorithm(), dtCollector);
vector<UsageData*> *usageDatas = dtCollector->getUnclassifiedData();
for (unsigned int k = 0; k < usageDatas->size(); k += 3) {
testUsageData = usageDatas->at(k);
if (testUsageData->isValid()) {
for (unsigned int j = 6; j < 18; j++) {
Timestamp timestamp = Timestamp(testUsageData->getDate().beginningOfSameDay().getRawTime() + j*3600);
answer = up->canRunGridApplication(timestamp, parameters, testUsageData);
cout << timestamp.formattedPrint() << "\t" << parameters << "\t" << answer << "\t";
vector<double> prediction = up->getPrediction(timestamp, CPU_USAGE, getPredictionHours(), testUsageData);
count = 0;
for (i = 0; i < prediction.size(); i++)
if (prediction[i] + parameters.getCpuUsage() <= 1.0f)
count++;
cout << (static_cast<double>(count) / prediction.size()) * 100 << "%\t";
count = 0;
for (i = 0; i < prediction.size(); i++) {
ResourceData rd = testUsageData->getData()[(timestamp.getSecondInDay()/COLLECT_INTERVAL) + SAMPLES_PER_DAY + i];
if (rd.isValid() && (rd.getCpuUsage() + parameters.getCpuUsage() <= 1.0f))
count++;
}
cout << (static_cast<double>(count) / prediction.size()) * 100 << "%\t";
cout << testUsageData->resourceAverage(CPU_USAGE, timestamp.getSecondInDay()/COLLECT_INTERVAL, timestamp.getSecondInDay()/COLLECT_INTERVAL + SAMPLES_PER_DAY) << endl;
}
}
}
/* informar qual cluster foi encontrado */
/* comparar resultado da predicao com o realizado */
/* pegar o resultado do getPrediction e ver a porcentagem de elementos do vetor de previsao condisseram
com o realizado */
return 0;
}
