创新创业理论研究与实践 ›› 2020, Vol. 3 ›› Issue (6): 179-180.

• 创新方法 • 上一篇    下一篇

云计算中的任务调度及重调度优化决策问题的研究

李国喜, 卢来, 赵男男   

  1. 广东海洋大学寸金学院,广东湛江 524094
  • 出版日期:2020-03-25 发布日期:2020-06-16
  • 作者简介:李国喜(1968-),男,湖南隆回人,硕士,讲师,研究方向:会计信息化与财务共享。
  • 基金资助:
    2018年广东省教育厅项目特色创新类项目-基于云平台的中小企业会计核算任务高度优化算法研究(项目编号:2018KTSCX333)

Research on the Optimal Decision of Task Scheduling and Rescheduling in Cloud Computing

LI Guoxi, LU Lai, ZHAO Nannan   

  1. Cunjin College, Guangdong Ocean University, Zhanjiang Guangdong,524094,China
  • Online:2020-03-25 Published:2020-06-16

摘要: 云计算是分布式计算,通过网络解决任务分发,并进行计算结果的合并。具体来说,在这个环境下,首先把用户提交的作业进行初始化,其次根据用户提交时间和优先级调度选择适当的策略将作业插入执行队列中,最后任务调度程序将从中选择的作业进行分割并分配到各个节点。某些节点的运行负载可能会超过自身的临界值,数值分析时收敛速度也较为缓慢,为有效解决这些问题,该文对调度算法和优化进行了深入的研究。

关键词: 云计算, 任务调度, 调度优化, 决策问题

Abstract: Cloud computing is distributed computing, which solves tasks through the network and merges computing results. Specifically, in this environment, the user-submitted jobs are first initialized, then the jobs are inserted into the execution queue according to the user-submitted time and priority scheduling according to the appropriate policy, and finally the jobs selected from the task scheduler are segmented and assigned to each node. The running load of some nodes may exceed their critical value, and the convergence speed is relatively slow in numerical analysis. In order to effectively solve these problems, this paper conducts in-depth research on scheduling algorithm and optimization.

Key words: Cloud computing, Task scheduling, Scheduling optimization, Decision making problems

中图分类号: