首页> 外文会议>IEEE International Conference on Big Data >Highly consolidated servers with container-based virtualization
【24h】

Highly consolidated servers with container-based virtualization

机译:具有基于容器的虚拟化的高度整合的服务器

获取原文

摘要

A huge number of inter-connected computers run in data centers. These computers consume large amount of power. Server consolidation with virtualization is a popular method to address this problem. The more computers are consolidated, the more energy is saved. However, highly consolidating, wherein many servers are consolidated into one physical computer, may result in large performance decline. Achieving high consolidation without large performance decline is important. Container-based operating system virtualization is an emerging method for constructing low-overhead virtualized environment. In this work, we focus on Docker, a popular container-based virtualizing system, and investigate its performance, especially performance in highly consolidated environment. First, we compare the performance with and without container-based virtualization, then show that container-based virtualization can provide similar performance to that without virtualization in CPU processing and networking but cannot provide comparable performance in I/O processing with the default setup. Second, we explore the relationship between the number of containers and the obtained performance. We then demonstrate that the I/O performance severely decreases as the number of consolidated servers increase. Third, we discuss the reason why the I/O performance drops largely and applications of highly consolidated servers.
机译:数据中心中运行着大量相互连接的计算机。这些计算机消耗大量电能。通过虚拟化进行服务器整合是解决此问题的一种流行方法。整合的计算机越多,节省的能源就越多。但是,高度整合(其中将许多服务器整合到一台物理计算机中)可能会导致性能大幅下降。在不大幅降低性能的情况下实现高整合非常重要。基于容器的操作系统虚拟化是一种用于构建低开销虚拟化环境的新兴方法。在这项工作中,我们将重点研究Docker(一种流行的基于容器的虚拟化系统),并研究其性能,尤其是高度整合的环境中的性能。首先,我们比较使用和不使用基于容器的虚拟化的性能,然后证明基于容器的虚拟化可以提供与不使用虚拟化的CPU处理和网络性能类似的性能,但是在默认设置下无法提供可比的I / O处理性能。其次,我们探索了容器数量与获得的性能之间的关系。然后,我们证明随着合并服务器数量的增加,I / O性能会严重下降。第三,我们讨论I / O性能大幅下降的原因以及高度整合的服务器的应用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号