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首页> 外文期刊>International journal of applied decision sciences >Task scheduling optimisation algorithm based on load balance under the cloud computing environment
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Task scheduling optimisation algorithm based on load balance under the cloud computing environment

机译:云计算环境下基于负载均衡的任务调度优化算法

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摘要

In order to achieve an optimal task scheduling scheme with the constraint of load balance in cloud computing platform. We utilise the CloudSim simulator to construct the cloud computing environment, and CloudSim contains three components: 1) CloudSim core simulation engine; 2) CloudSim basic structure; 3) user codes. Afterwards, we propose a novel load balancing oriented task scheduling optimisation algorithm based on genetic algorithm, and task assignment results are obtained through analysing gene values of chromosomes. In order to ensure convergence rate in genetic algorithm, we design the fitness function by integrating computation time and computation cost together. Furthermore, we design adaptive crossover and mutation operations to promote the search efficiency. Finally, we conduct an experiment to demonstrate the performance of the proposed algorithm. The experimental results show that the proposed algorithm can achieve the goal of high level of load balance with lower calculation time and cost.
机译:为了在云计算平台中实现具有负载均衡约束的最优任务调度方案。我们利用CloudSim模拟器构建云计算环境,CloudSim包含三个组件:1)CloudSim核心模拟引擎; 2)CloudSim基本结构; 3)用户代码。然后,提出了一种基于遗传算法的面向负载均衡的任务调度优化算法,并通过分析染色体的基因值获得任务分配结果。为了保证遗传算法的收敛速度,我们通过综合计算时间和计算成本来设计适应度函数。此外,我们设计了自适应交叉和变异操作,以提高搜索效率。最后,我们进行了实验以证明所提出算法的性能。实验结果表明,该算法能够以较低的计算时间和成本实现较高的负载均衡水平。

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