An Overview of the State-of-the-art Virtual Machine Placement Algorithms for Green Cloud Data Centres

Anindya Bose, S. Nag
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Abstract

Increased energy consumption in Cloud Data Centres (CDCs) increases the carbon footprint. Efficiency of the data centres thus needs to be improved through server consolidation using effective virtual machine (VM) placement and migration techniques and minimizing the number of active physical machines (PMs). One of the problems is how to operationally allocate the VMs to PMs. These allocations have both operational costs and energy consumption issues. To achieve the aim of ‘Green Computing’ a number of state-of-the-art machine learning algorithms have been proposed for the VM placement. The authors of this paper have provided a detailed discussion and comparison of some of the current research works on energy efficiency. and cons of each of these techniques have been discussed. Some future research prospects in this field have also been mentioned at the end.
绿色云数据中心最先进的虚拟机放置算法概述
云数据中心(cdc)能源消耗的增加增加了碳足迹。因此,数据中心的效率需要通过使用有效的虚拟机(VM)放置和迁移技术进行服务器整合来提高,并尽量减少活动物理机(pm)的数量。其中一个问题是如何在操作上将虚拟机分配给pm。这些分配存在运营成本和能源消耗问题。为了实现“绿色计算”的目标,已经提出了许多最先进的机器学习算法来放置虚拟机。本文作者对目前一些关于能源效率的研究工作进行了详细的讨论和比较。并且讨论了每种技术的缺点。最后对该领域未来的研究前景进行了展望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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