Impact of Virtualization on Cloud Computing Energy Consumption: Empirical Study

Abstract

Global warming, which is currently one of the greatest environmental challenges, is caused by carbon emissions. A report from the Energy Information Administration indicates that approximately 98% of CO2 emissions can be attributed to energy consumption. The trade-off between efficient and ecologically sound operation represents a major challenge faced by many organizations at present. In addition, numerous companies are currently compelled to pay a carbon tax for the resources they use and the environmental impact of their products and services. Therefore, an energy consumption system can generate actual financial payback. Green information technology involves various approaches, including power management, recycling, telecommunications, and virtualization. This paper focuses on comparing and evaluating techniques used for reducing energy consumption in virtualized environments. We first highlight the impact of virtualization techniques on minimizing energy consumption in cloud computing. Then we present an experimental comparative study between two common energy-efficient task scheduling algorithms in cloud computing (i.e., the green scheduler, the power saver scheduler). These algorithms are discussed briefly and analyzed. The three metrics used to evaluate the task scheduling algorithms are (1) total power consumption, (2) data center load, and (3) virtual machine load. This work aims to gauge and subsequently improve energy consumption efficiency in virtualized environments.