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A Resource Co-Allocation method for load-balance scheduling over big data platforms

机译:大数据平台上负载均衡调度的资源协同分配方法

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摘要

Recently, an increasingly large number of high-performance computing (HPC) applications have been developed and hosted in clouds. The cloud computing scheme provides a model of utility computing, which is often implemented in the form of big data centers. As HPC applications are usually resource-intensive, how to exploit economies of scale to harmonize the resource allocation among large-scale HPC applications under performance constraints often poses a significant challenge on the load-balance scheduling policies in big data platforms. In view of this challenge, in this paper we propose aResourceCo-Allocation method, named RCA, for load-balance scheduling. Technically, the method is promoted by four steps that are enacted in a hierarchical control framework. The effectiveness and efficiency of the proposed method are validated by extensive experiments.
机译:最近,越来越多的高性能计算(HPC)应用程序已经开发并托管在云中。云计算方案提供了效用计算模型,该模型通常以大数据中心的形式实现。由于HPC应用程序通常是资源密集型的,因此在性能约束下如何利用规模经济来协调大型HPC应用程序之间的资源分配通常会对大数据平台中的负载平衡调度策略提出重大挑战。鉴于这一挑战,在本文中,我们提出了一种用于负载均衡调度的资源共享分配方法,称为RCA。从技术上讲,该方法是通过在分层控制框架中制定的四个步骤来促进的。通过大量实验验证了该方法的有效性和有效性。

著录项

  • 来源
    《Future generation computer systems》 |2018年第9期|1064-1075|共12页
  • 作者单位

    State Key Laboratory for Novel Software Technology, Nanjing University;

    Jiangsu Engineering Center of Network Monitoring, Nanjing University of Information Science and Technology;

    State Key Laboratory for Novel Software Technology, Nanjing University;

    Department of Computer Science, St. Francis Xavier University,Cyber-Physical-Social Systems (CPSS) Lab, School of Computer Science and Technology, Huazhong University of Science and Technology;

    State Key Laboratory for Novel Software Technology, Nanjing University;

  • 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

    Cloud computing; Big data; Load balance; Resource allocation;

    机译:云计算;大数据;负载均衡;资源分配;

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