Task duplication-based workflow scheduling for heterogeneous cloud environment

Indrajeet Gupta, M. Kumar, P. K. Jana
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引用次数: 12

Abstract

Workflow scheduling is a well-known NP-complete problem. As per the nature of the workflow scheduling for cloud computing environment researchers are dedicated to find out the optimal or near optimal solution based on different heuristics. Another key issue in the recent years is handling workflow in heterogeneous cloud system that is paying significant consideration of the research community. In this paper, we propose a task duplication-based workflow scheduling algorithm for heterogeneous cloud environment which is centered on task duplication realization. The proposed algorithm has two phases. The first phase computes the priority of all the tasks and second phase goes through the scheduling with task duplication by calculating data arrival time from one task to another task. Proposed algorithm aims to minimize workflow execution time and to maximize the resource utilization. The performance evaluation of the proposed algorithm is done on benchmark scientific workflow applications with different task-cloud heterogeneity. Comparisons of the simulated results with the some existing workflow scheduling algorithms noticeably show that the proposed algorithm outpaces in terms of makespan and average cloud utilization.
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异构云环境下基于任务重复的工作流调度
工作流调度是一个众所周知的np完全问题。针对云计算环境下工作流调度的特点,研究人员致力于利用不同的启发式方法找出最优或接近最优的解决方案。异构云系统中的工作流处理是近年来备受学术界关注的另一个关键问题。本文提出了一种以任务复制实现为核心的异构云环境下基于任务复制的工作流调度算法。该算法分为两个阶段。第一阶段计算所有任务的优先级,第二阶段通过计算从一个任务到另一个任务的数据到达时间来进行任务重复调度。该算法旨在最小化工作流执行时间和最大化资源利用率。在具有不同任务云异构性的基准科学工作流应用中对该算法进行了性能评估。将仿真结果与现有的工作流调度算法进行了比较,结果表明该算法在makespan和平均云利用率方面明显优于现有算法。
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