Analyzing the impact of provisioning overhead time in cloud computing centers

In this paper, we analyze an efficient pool management model for cloud systems that partitions the servers (physical machines) into a hot and cold pool to improve energy efficiency. Servers are moved them from one pool to the other as needed to fulfill the incoming task requests, which are provisioned on virtual machines running on the servers. The model features two levels of task admission control: one at the global input, the other at each server separately. We examine the behavior of the cloud system in the regions of linear operation, transition to saturation and saturation, from the viewpoint of task rejection rates and energy consumption. Furthermore, we evaluate the sensitivity of task blocking probability and energy consumption to the pool partitioning threshold and the value of mean look up time in hot and cold pools, respectively, in different test scenarios.