In this research project, we intend to collect real-time network traffic data and run machine learning algorithms to see whether non-overlapping clusters exist. If distinct clusters do exist, we continue to find the optimal number of clusters and assign labels to the data points that will be used for classification. We use three methods of classification: KNN Classifier, Artificial Neural Networks, and Decision Tree. Labeling and classifying our dataset is essential for scheduling purposes.