Abstract
Dynamic capacity provisioning is a useful technique for handling the workload variations seen in cloud environment. In this paper, we propose a dynamic provisioning technique for multi-tier applications to allocate resources efficiently using queueing model. It dynamically increases the mean service rate of the virtual machines to avoid congestion in the multi-tier environments. An optimization model to minimize the total number of virtual machines for computing resources in each tier has been presented. Using the supplementary variable and the recursive techniques, we obtain the system-length distributions at pre-arrival and arbitrary epochs. Some important performance indicators such as blocking probability, request waiting time and number of tasks in the system and in the queue have also been investigated. Finally, computational results showing the effect of model parameters on key performance indicators are presented.