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Multijob Associated Task Scheduling for Cloud Computing Based on Task Duplication and Insertion
Wireless Communications and Mobile Computing ( IF 2.146 ) Pub Date : 2021-04-28 , DOI: 10.1155/2021/6631752
Lei Shi 1 , Jing Xu 1 , Lunfei Wang 1 , Jie Chen 1 , Zhifeng Jin 1 , Tao Ouyang 1 , Juan Xu 1 , Yuqi Fan 1
Affiliation  

With the emergence and development of various computer technologies, many jobs processed in cloud computing systems consist of multiple associated tasks which follow the constraint of execution order. The task of each job can be assigned to different nodes for execution, and the relevant data are transmitted between nodes to complete the job processing. The computing or communication capabilities of each node may be different due to processor heterogeneity, and hence, a task scheduling algorithm is of great significance for job processing performance. An efficient task scheduling algorithm can make full use of resources and improve the performance of job processing. The performance of existing research on associated task scheduling for multiple jobs needs to be improved. Therefore, this paper studies the problem of multijob associated task scheduling with the goal of minimizing the jobs’ makespan. This paper proposes a task Duplication and Insertion algorithm based on List Scheduling (DILS) which incorporates dynamic finish time prediction, task replication, and task insertion. The algorithm dynamically schedules tasks by predicting the completion time of tasks according to the scheduling of previously scheduled tasks, replicates tasks on different nodes, reduces transmission time, and inserts tasks into idle time slots to speed up task execution. Experimental results demonstrate that our algorithm can effectively reduce the jobs’ makespan.

中文翻译:

基于任务复制和插入的云计算多作业关联任务调度

随着各种计算机技术的出现和发展,云计算系统中处理的许多作业都由多个相关联的任务组成,这些任务遵循执行顺序的约束。每个作业的任务可以分配给不同的节点以执行,并且相关数据在节点之间传输以完成作业处理。由于处理器的异构性,每个节点的计算或通信能力可能会有所不同,因此,任务调度算法对于作业处理性能具有重要意义。高效的任务调度算法可以充分利用资源,提高作业处理的性能。需要改进现有研究中与多个任务相关联的任务调度的性能。所以,本文研究了与多作业相关的任务调度问题,目的是最大程度地减少作业的工期。本文提出了一种基于列表调度(DILS)的任务复制和插入算法,该算法融合了动态完成时间预测,任务复制和任务插入。该算法通过根据先前计划的任务的调度来预测任务的完成时间来动态地调度任务,在不同节点上复制任务,减少传输时间,并将任务插入空闲时隙以加快任务执行速度。实验结果表明,该算法可以有效地减少作业的工期。本文提出了一种基于列表调度(DILS)的任务复制和插入算法,该算法融合了动态完成时间预测,任务复制和任务插入。该算法通过根据先前计划的任务的调度来预测任务的完成时间来动态地调度任务,在不同节点上复制任务,减少传输时间,并将任务插入空闲时隙以加快任务执行速度。实验结果表明,该算法可以有效地减少作业的工期。本文提出了一种基于列表调度(DILS)的任务复制和插入算法,该算法融合了动态完成时间预测,任务复制和任务插入。该算法通过根据先前计划的任务的调度来预测任务的完成时间来动态地调度任务,在不同节点上复制任务,减少传输时间,并将任务插入空闲时隙以加快任务执行速度。实验结果表明,该算法可以有效地减少作业的工期。并将任务插入空闲时隙以加快任务执行速度。实验结果表明,该算法可以有效地减少作业的工期。并将任务插入空闲时隙以加快任务执行速度。实验结果表明,该算法可以有效地减少作业的工期。
更新日期:2021-04-29
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