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A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

机译:用于数据中心节能虚拟机放置问题的混合遗传算法

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摘要

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.
机译:使用虚拟化技术的服务器整合已成为提高数据中心能效的重要技术。虚拟机放置是服务器整合技术的关键。在过去的几年中,已经提出了许多虚拟机放置方法。但是,现有的虚拟机放置方法仅考虑物理机的能耗,而没有考虑数据中心通信网络中的能耗。但是,数据中心通信网络中的能耗并非微不足道,因此应在虚拟机放置中考虑。在我们的初步研究中,我们针对新的虚拟机放置问题提出了一种遗传算法,该问题考虑了物理机和数据中心通信网络中的能耗。为了提高遗传算法的性能和效率,提出了一种混合遗传算法,用于节能虚拟机的放置问题。实验结果表明,混合遗传算法明显优于原始遗传算法,并且具有可扩展性。

著录项

  • 作者

    Tang Maolin; Pan Shenchen;

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  • 年度 2015
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