Performance Evaluation of Energy Efficient Power Models for Digital Cloud

Background: To improve quality of service energy-efficiency is one of the key parameters of Cloud service providers. Every year huge amounts of electrical energy consume by Cloud data center which leads to more expense in costs and emission of CO2 to the environment which is unhealthy for us. In this case the need of Green Cloud computing solutions to minimize emission of carbon footprints as well as operational costs is the utmost desire. Objectives: In our research work we have implemented four different power models such as linear model, cubic model, square model and square ischolar_main model on an Infrastructure-as-a-Service (IaaS) Cloud environment to find out the best one. Methods: Here we considered the CPU utilization and power consumption by enabling virtual machine migration. Then to validate the accuracy of these power models R-squared, Mean Square Error (MSE) have been performed. Finding: We found out that the cubic polynomial model is the most efficient one and consume less power in comparison to the other three models. Application: Hence this model can be used in energy saving applications over Cloud data centers.