Dynamically Fine-grained Scheduling Method in Cloud Environment
Author:
Affiliation:

Clc Number:

Fund Project:

National Key Research and Development Program of China (2016YFB0200902); National Natural Science Foundation of China (61572394)

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    The coarse-grained scheduling used in cloud computing platform allocates fixed quantity resources to tasks. However, this allocation can easily lead to problems such as resource fragmentation, over-commitment and inefficient resource utilization. This study proposes a dynamically fine-grained scheduling method to resolve those problems. This method estimates resource requirement of task according to similar tasks and divides tasks into execution stages according to the task requirement, and it also matches task resource requirement and available server resources by stages to refine two aspects of allocation granularity: allocation duration and allocation quantity. Furthermore, this method may compress resource allocation to further improve resource utilization and performance, and this method uses several mechanisms including runtime resource monitoring, allocation policy adjustments, and scheduling constraint checks to ensure resource utilization and performance of cloud computing platform. Based on this method, a scheduler has been implemented in the open source cloud computing platform Yarn. The test results show that the dynamically fine-grained scheduling method can resolve resource allocation problems by significantly improving resource utilization and performance with acceptable fairness and scheduling response times.

    Reference
    Related
    Cited by
Get Citation

周墨颂,董小社,陈衡,张兴军.一种云环境中的动态细粒度资源调度方法.软件学报,2020,31(12):3981-3999

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:October 16,2017
  • Revised:June 20,2018
  • Adopted:
  • Online: December 03,2020
  • Published: December 06,2020
You are the firstVisitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-4
Address:4# South Fourth Street, Zhong Guan Cun, Beijing 100190,Postal Code:100190
Phone:010-62562563 Fax:010-62562533 Email:jos@iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063