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WBAT Job Scheduler: A Multi-Objective Approach for Job Scheduling Problem on Cloud Computing

机译:WBAT Job Scheduler:云计算上的作业调度问题的多目标方法

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The main objective of the proposed methodology is multi-objective job scheduling using hybridization of whale and BAT optimization algorithm (WBAT) which is used to change existing solution and to adopt a new good solution based on the objective function. The scheduling function in the proposed job scheduling strategy first creates a set of jobs and cloud node to generate the population by assigning jobs to cloud node randomly and evaluate the fitness function which minimizes the makespan and maximizes the quality of jobs. Second, the function uses iterations to regenerate populations based on WBAT behavior to produce the best job schedule that gives minimum makespan and good quality of jobs. The experimental results show that the performance of the proposed methods is better than the other methods of job scheduling problems.
机译:所提出的方法的主要目的是使用鲸鱼和蝙蝠优化算法(WBAT)的杂交来改变现有解决方案的多目标作业调度,并根据目标函数采用新的良好解决方案。所提出的作业调度策略中的调度函数首先创建一组作业和云节点,以便随机将作业分配给云节点并评估最小化Mapspan的健身功能并最大化作业质量的群体。其次,该函数使用迭代基于WBAT行为来重新生成群体,以产生最佳的工作时间表,以提供最低的Mapspan和良好的工作质量。实验结果表明,所提出的方法的性能优于其他工作调度问题的方法。

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