Server Workload Classification and Analysis with Machine Learning Algorithms

The main factor in measuring server performance isthe accuracy of detection mechanisms. Sever is neededto detect server overload condition accurately.Therefore, it can be satisfied customers by reducingrequest drop rate. Server overload detection would bean initial step of overload control system. In order toprovide such a detection mechanism, it is important tochoose the best classifier which is the most suitable forour dataset. Selecting correct classifier maximize theperformance of detection mechanism.In this paper, we present how server workloadclassification task is performed by using differentmachine learning classification methods and how thebest classifier improve overload detection mechanism.We make a synthetic dataset by using windowperformance monitor tool. Many classifiers areevaluated over synthetic dataset