Effect of Human Learning on Performance of Cloud Applications

End users of cloud applications range from novice to expert depending on how experienced they are in using them. With repeated usage of an application, a user's think time gradually decreases, known as human learning phenomenon. This decrease impacts the system workload thereby affecting the application's transient performance. However, such impact of human learning on system performance has never been accounted for. In this work we propose a closed queueing network model that accounts for human learning in analyzing the transient performance of a tiered cloud application. We solve the model using discrete event simulation. The model results show that the lack of accountability of human learning may lead to incorrectly selecting a virtual machine configuration that fails to meet the system response time requirement.