Abstract
Data centers are today the technological backbone for any company. However, the failure to control energy consumption leads to very high operating costs and carbon dioxide emissions. On the other hand, reducing power consumption in data centers can lead to a degradation of application performance and quality of service in terms of SLA Service Level Agreement. It is therefore essential to find a compromise in terms of energy efficiency and resource consumption. This paper highlights the different approaches of energy management, related studies, algorithms used, the advantages and weaknesses of each approach related to server virtualization, consolidation and deconsolidation of virtual machines.
Highlights
Technological advances and new business models of cloud computing have contributed to the development of data centers in number and size.This strong growth has contributed to an increase in the cost of electricity and enormous energy consumption, but has generated significant carbon dioxide emissions, contributing to the greenhouse effect [1]
In some cases [1], such as an Infrastructure as a service (IaaS) data center, the knowledge of application workloads and the time during which virtual machines are used is unknown, which helps to depend on processor performance
In this paper we focused on dynamic energy management at the software level by applying virtualization, consolidation and deconsolidation techniques to virtual machines
Summary
Technological advances and new business models of cloud computing have contributed to the development of data centers in number and size. This strong growth has contributed to an increase in the cost of electricity and enormous energy consumption, but has generated significant carbon dioxide emissions, contributing to the greenhouse effect [1]. Data centers' energy costs are increasing, which requires reducing their energy consumption and improving energy efficiency through the development of efficient management approaches.
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