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High-performance docker integration scheme based on OpenStack

机译:基于OpenStack的高性能Docker集成方案

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摘要

As an emerging technology in cloud computing, Docker is becoming increasingly popular due to its high speed, high efficiency and portability. The integration of Docker with Open-Stack has been a hot topic in research and industrial areas, e.g., as an emulation platform for evaluating cyberspace security technologies. This paper introduces a high-performance Docker integration scheme based on OpenStack that implements a container management service called Yun. Yun interacts with OpenStack's services and manages the lifecycle of the container through the Docker Engine to integrate OpenStack and Docker. Yun improves the container deployment and throughput as well as the system performance by optimizing the message transmission architecture between internal components, the underlying network data transmission architecture between containers, and the scheduling methods. Based on the Docker Engine API, Yun provides users with interfaces for CPU, memory and disk resource limits to satisfy precise resource limits. Regarding scheduling, Yun introduces a new NUMA-aware and resource-utilization-aware scheduling model to improve the performance of containers under resource competition and to balance the load of computing resources. Simultaneously, Yun decouples from OpenStack versions by isolating its own running environment from the running environment of OpenStack to achieve better compatibility. Experiments show that compared to traditional methods, Yun not only achieves the integration of Open-Stack and Docker but also exhibits high performance in terms of deployment efficiency, container throughput and the container's system while also achieving load balancing.
机译:由于云计算中的新兴技术,由于其高速,高效率和便携性,Docker变得越来越受欢迎。 Docker与开放式堆栈的集成是研究和工业领域的热门话题,例如,作为评估网络空间安全技术的仿真平台。本文介绍了一种基于OpenStack的高性能Docker集成方案,实现了一个名为Yun的容器管理服务。 Yun与OpenStack的服务进行互动,并通过Docker引擎管理容器的生命周期,以集成OpenStack和Docker。 yun通过优化内部组件之间的消息传输架构,容器之间的底层网络数据传输架构和调度方法来提高集装箱部署和吞吐量以及系统性能。基于Docker Engine API,Yun为用户提供CPU,内存和磁盘资源限制的接口,以满足精确的资源限制。关于调度,Yun介绍了一种新的Numa感知和资源利用所感知的调度模型,以提高资源竞争下的容器性能,并平衡计算资源的负载。同时,通过将自己的运行环境从OpenStack的运行环境隔离以实现更好的兼容性来同时,yun从OpenStack版本中解耦。实验表明,与传统方法相比,云不仅达到了开放式堆叠和码头的集成,而且在部署效率,集装箱吞吐量和容器系统方面也表现出高性能,同时也实现了负载平衡。

著录项

  • 来源
    《World Wide Web》 |2020年第4期|2593-2632|共40页
  • 作者单位

    School of Internet of Things Engineering Jiangnan University Wuxi Jiangsu Province China;

    School of Internet of Things Engineering Jiangnan University Wuxi Jiangsu Province China Cyberspace Security Research Center. Peng Cheng Laboratory Shenzhen Guangdong Province China;

    School of Internet of Things Engineering Jiangnan University Wuxi Jiangsu Province China;

    School of Cyberspace Security Beijing University of Posts and Telecommunications Beijing China;

    School of Internet of Things Engineering Jiangnan University Wuxi Jiangsu Province China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Cloud computing; OpenStack; Docker; Virtualization;

    机译:云计算;OpenStack;Docker;虚拟化;

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