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A balanced virtual machine scheduling method for energy-performance trade-offs in cyber-physical cloud systems

机译:一种在网络物理云系统中权衡性能的平衡虚拟机调度方法

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摘要

The cloud computing scheme promises many salient features such as on-demand resource provisioning to users, and it therefore has drawn significant attention from the cyber-physical systems (CPS). An increasing number of CPS have been deployed in cloud platforms, and to accommodate numerous CPS applications, cloud datacenters often consist of a huge number of physical computation and storage nodes, and the number is still increasing. As a result, the electricity power consumption in cloud datacenters is considerable, currently accounting for about 1.3% of the worldwide electricity. How to reduce the energy consumption of datacenters is an economically beneficial but challenging problem. Optimizing virtual machine (VM) scheduling in datacenters by live VM migration is an appealing method to save energy consumption. However, it is still a challenge to conduct VM scheduling in an energy-efficient and performance-guaranteed manner, since VM migration can suffer from severe performance degradation while saving energy. In this paper, we propose a balanced VM scheduling method to achieve tradeoffs between energy and performance in cyber-physical cloud systems. Specifically, the problem is formulated via a joint optimization model, and a balanced VM scheduling method is proposed accordingly to determine which VMs and where should be migrated, aiming at both reducing energy consumption and mitigating performance degradation. Both analytical and simulation results demonstrate the effectiveness and efficiency of our method.
机译:云计算方案承诺了许多显着的功能,例如向用户提供按需资源,因此,它已引起了网络物理系统(CPS)的极大关注。在云平台上已经部署了越来越多的CPS,并且为了适应众多CPS应用程序,云数据中心通常由大量的物理计算和存储节点组成,并且数量还在不断增加。结果,云数据中心的电力消耗相当可观,目前约占全球电力消耗的1.3%。如何减少数据中心的能耗是经济上有益但具有挑战性的问题。通过实时VM迁移来优化数据中心中的虚拟机(VM)调度是一种节省能耗的吸引人的方法。但是,以高效节能和性能保证的方式进行VM调度仍然是一个挑战,因为VM迁移在节省能源的同时会遭受严重的性能下降。在本文中,我们提出了一种平衡的VM调度方法,以实现网络物理云系统中能量和性能之间的折衷。具体而言,通过联合优化模型解决问题,并提出了一种平衡的虚拟机调度方法,以确定哪些虚拟机以及应在何处迁移,以减少能耗并减轻性能下降。分析和仿真结果均证明了该方法的有效性和效率。

著录项

  • 来源
    《Future generation computer systems》 |2020年第4期|789-799|共11页
  • 作者

  • 作者单位

    School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China;

    Department of Electrical & Computer Engineering The University of Auckland Auckland NewZealand;

    State Key Laboratory for Novel Software Technology Nanjing University Nanjing China;

    School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China;

    School of Information Technology Deakin University Melbourne Australia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Balanced VM scheduling; Energy; Performance; CPS; Cloud;

    机译:均衡的虚拟机调度;能源;性能;CPS;云;

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