计算机工程 ›› 2019, Vol. 45 ›› Issue (3): 7-13.doi: 10.19678/j.issn.1000-3428.0049811

所属专题: 云计算与大数据专题

• 云计算与大数据专题 • 上一篇    下一篇

云环境下支持弹性伸缩的容器化工作流框架

刘彪,王宝生,邓文平   

  1. 国防科技大学 计算机学院,长沙 410073
  • 收稿日期:2017-12-22 出版日期:2019-03-15 发布日期:2019-03-15
  • 作者简介:刘彪(1993—),男,硕士研究生,主研方向为云计算、大数据、并行计算;王宝生,研究员、博士生导师;邓文平,助理研究员、博士。
  • 基金项目:

    国家自然科学基金(61472438,61602503)。

Containerized Workflow Framework Supporting Elastic Scaling in Cloud Environment

LIU Biao,WANG Baosheng,DENG Wenping   

  1. School of Computer,National University of Defense Technology,Changsha 410073,China
  • Received:2017-12-22 Online:2019-03-15 Published:2019-03-15

摘要:

云计算和容器技术为工作流的运行带来便利,但其存在管理困难、资源利用率不足以及智能和自动化程度较低等问题。为此,提出一种支持弹性伸缩的容器化工作流框架,在此基础上给出基于CPU使用率的工作流自动伸缩模型,在流程过载时自动扩充流程的容器数目,减少任务等待时间,当任务负载减小时,能够在确保任务不丢失的情况下完成流程的缩容,以节约资源和成本。实验结果表明,流程的扩容数量与其处理时间成正相关,较好地消除工作流中的瓶颈,在工作流过载时,能够以较短的时间完成相同的任务量。

关键词: 云计算, Docker容器, 工作流框架, 弹性伸缩, 调度策略, 负载均衡

Abstract:

Cloud computing and container technology bring the convenience of the workflows operation,but there are problems such as management difficulties,insufficient resource utilization,and low intelligence and automation.Therefore,a containerized workflow framework supporting elastic scaling is proposed.On the basis of this,a workflow automatic scaling model based on CPU usage is presented,which can automatically expand the number of containers when the workflow process is overloaded,and reduce the task waiting time.When the task load is reduced,the process can be reduced while ensuring that the task is not lost to save resources and costs.Experimental results show that the number of expansions of the process is positively related to the processing time,which can better eliminate the bottleneck of the workflow.When the workflow is overloaded,the same amount of tasks can be completed in a shorter time.

Key words: cloud computing, Docker container, workflow framework, elastic scaling, scheduling strategy, load balancing

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