利用深度优先启发的机会探索改进云计算环境中的虚拟机迁移效果

K.Akhil Kumar, Jyoti Thaman
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引用次数: 1

摘要

云平台已经成为IT外包的事实上的标准。这导致基础设施和开发平台从内部大规模迁移到云服务提供商。最近关于云平台的许多建议都解决了云地平线上出现的几个问题。在迁移或重新分配虚拟机后,虚拟机放置(VMP)一直是一个严重的问题。最近的大多数工作都缺乏多虚拟机放置(MVMP)问题实例。本文提出了一种新的基于深度优先机会探测(DFOE)的MVMP思想。将该算法的性能与现有的单虚拟机放置基准算法进行了比较。通过模拟实时负载场景,报告了在虚拟机迁移数量、能耗和虚拟机重新分配方面的改进。云环境可以从MVMP中受益,并在节能和负载平衡方面提高运营利润率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Virtual Machine Migration Effects in Cloud Computing Environments Using Depth First Inspired Opportunity Exploration
The cloud platform has established itself as the de-facto standard in IT outsourcing. This is resulting in large-scale migration of infrastructure and development platforms from in-house to cloud service providers. Many recent proposals on cloud platforms have addressed several issues that appeared on the cloud horizon. VM placement (VMP) has been a serious concern when it comes to placement of VMs after migration or VM reallocation. Most of the recent works have lacked multiple VM placement (MVMP) problem instances. A recently researched idea of MVMP through depth first opportunistic exploration (DFOE) is proposed in this paper. The performance of MVMP is compared with existing single VM placement benchmark algorithm. Improvement in terms of number of VM migrations, energy consumption, and VM reallocation is reported through simulation of real-time load scenario. Cloud environments can benefit from MVMP and improve operating margins in terms of power saving and load balancing.
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