# Server Operation and Virtualization to Save Energy and Cost in Future Sustainable Computing
## 2 Background  
There is an assumption that the volume of CO\({}_{2}\) emissions incurring from Information Technology is equivalent to those from the aviation industry. The increased demand of the cloud service is pushing data centers to the limit but forcing them to achieve green computing at the same time [1]. Not long ago, Google's chief executive officer emphasized this by saying, \"What matters most to the computer designers at Google is not speed but power, low power, because data centers can consume as much energy as a city\" [2]. Recently, the cloud service is gaining popularity as one of the most convenient IT services such that more power is required to meet the demand. Also, the sales of high-definition multimedia are increasing rapidly along with other sophisticated computer hardware. These phenomena have forced internet providers to seek a more efficient power management strategy for their data centers and consider using renewable energy sources to reduce operational cost while avoiding adverse effects on the environment. Such a challenge is also affecting algorithm development. The United States Data Center Energy Usage Report [3] (Lawrence Berkeley National Laboratory, for U.S. Department of Energy) issued in 2016 specifically mentioned that the data centers in the US had consumed approximately 70 billion kWh in 2014, equivalent to roughly 1.8% of the total electricity used in the US in the same year. The total volume of global CO\({}_{2}\) emissions generated from the IT industry is almost equivalent to the volume generated from the aviation industry in 2011 (70.9 MMTCO\({}_{2}\)) [4; 5]. It is interesting that some energy efficiency schemes were actually successful in preventing or at least slowing down the increase in power demand despite the rapid and significant increase in big data. That is, the power consumptions in data centers increased approximately 4% during the period of four years (2010-2014) compared with the 24% and 90% increase in the previous five-year period and in another five-year period before that, respectively. It is being considered that the major underlying cause of recent power demand increase is the growing number of hyper-scale data centers exclusive to big cloud facilities. As such, power-efficient techniques and algorithms are essential for controlling the power usage in the ever-growing IT environment [6]. Virtualization was discussed in the research work Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud by [PERSON] et al. [7]. The ever-increasing demand for cloud service is compelling internet providers to construct large-scale virtualized data centers equipped with virtual machines. The some of the replication techniques were applied to reduce the possibility of service failure and the trade-offs between task completion time and energy use in the varied replication methods were determined by the comprehensive analytical models which grasp the state transitions of virtual machines as well as the power consumption patterns. Some of the issues pertaining to energy consumption were discussed from an application-level perspective in the article Characterizing Energy per Job in Cloud Applications by [PERSON] et al. [8], which proposed several effective analytical models for assessing energy consumption and estimate the energy-per-job status in data centers with different configurations. The research focuses on how efficient the applications are with respect to their performances and the energy consumed per job. In this case, the resources are to be shared and the hosts with virtual machines are heterogeneous in terms of energy profiles. Such an attempt was to determine the most efficient way of utilizing the resources given. Some of the energy-efficient pricing strategies are being discussed in the article Energy-Aware Pricing in a Three-Tiered Cloud Service Market by [PERSON] et al.