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Scheduling deadline-constrained scientific workflow using chemical reaction optimisation algorithm in clouds

机译:在云中使用化学反应优化算法调度截止日期约束的科学工作流程

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The advent of cloud computing as a new model of service provisioning in distributed systems encourages researchers to investigate its benefits and drawbacks on executing scientific applications such as workflows. One of the most challenging problems in clouds is workflow scheduling, i.e., the problem of satisfying the QoS requirements of the users as well as minimising the cost of workflow execution. In this paper, a novel meta-heuristic method, called chemical reaction optimisation (CRO), is developed to solve deadline-constrained workflow scheduling, which tries to minimise the cost of workflow execution while meeting a user-defined deadline. A set of appropriate parameters can be obtained based on orthogonal experimental design (OED) and factor analysis. Experiments are done in two real workflow applications, and the results demonstrate the effectiveness of the proposed algorithm.
机译:作为分布式系统中的新服务提供新模式的云计算的出现鼓励研究人员调查其对执行工作流程等科学应用的益处和缺点。 云中最具挑战性的问题之一是工作流程调度,即满足用户QoS要求的问题,以及最小化工作流执行的成本。 本文采用一种名为化学反应优化(CRO)的新型元启发式方法,以解决截止日期约束的工作流程调度,这试图最小化工作流程执行的成本,同时满足用户定义的截止日期。 可以基于正交实验设计(OED)和因子分析来获得一组适当的参数。 实验在两个实际工作流程应用中完成,结果证明了所提出的算法的有效性。

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