Simulating and Evaluating the Performance of a Cloud Computing Datacenter Using Queuing Model

Cloud computing and virtualization are fundamental to modern computer system design. As cloud computing adoption grows across organizations, evaluating its performance becomes essential. This study simulates and analyzes a cloud datacenter’s performance using queuing models. Specifically, an M<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</inf>/M/1/K queuing system is employed, with arrival parameters estimated from real CPU utilization data from the Bitbrains datacenter, modeled as discrete Homogeneous Poisson Processes (HPPs). The simulation results of the modeled system reveal minimal average waiting time and efficient task processing with low delays. Additionally, the study highlights the significant impact of service rates on the average response times of tasks arriving as discrete HPPs. These findings offer valuable insights into cloud datacenter performance, aiding in informed decisions for service upgrades and optimal resource utilization.