Scheduling is an important technique to improve the productivity of workflow applications in a grid system. Serving workflow applications added overhead on the scheduling system since the scheduler should choose the best zero-dependent job that improves the performance of a grid system. This paper proposes two dependent job scheduling algorithms based on analyzing the effect of categorical and continuous variables of the job, which are used in the calculation of job weight. To find the job weight, twostep clustering is used with 10 groups and the ranking equation. In addition, to verify the ability to apply the proposed algorithms in a real environment, weighted least squares estimation is used. The results showed that the prediction rate is equal to 99.88%, which indicates that the proposed algorithms could be applied in a real grid system with low overhead. Through simulations and after testing the proposed algorithms, the average results showed that the Dependent Job Scheduling (DJS) algorithm outperformed the previous algorithms, in total execution time and an average waiting time with an improvement value of 1.18 and 1.92 times, respectively. While DJS algorithm with weighting factor (DJSJP) outperformed the previous algorithms in total execution time only with an improvement value equal to 1.17 times. The overall results indicated that the proposed algorithms are efficient to be used in a grid system, besides four bits are sufficient to improve the performance of the job scheduling system.

中文翻译：

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基于两步聚类和最小作业权重的工作流作业调度

调度是提高网格系统中工作流应用程序生产力的重要技术。服务工作流应用程序增加了调度系统的开销，因为调度程序应该选择最佳的零依赖作业来提高网格系统的性能。本文在分析作业的分类变量和连续变量的影响的基础上，提出了两种依赖作业调度算法，用于作业权重的计算。为了找到工作权重，两步聚类使用了 10 个组和排名方程。此外，为了验证在实际环境中应用所提出算法的能力，使用了加权最小二乘估计。结果表明，预测率等于99.88%，这表明所提出的算法可以以低开销应用于真实的网格系统。通过仿真和对所提出算法的测试，平均结果表明，依赖作业调度（DJS）算法在总执行时间和平均等待时间方面优于以前的算法，改进值分别为 1.18 和 1.92 倍。而带有加权因子的 DJS 算法（DJSJP）在总执行时间上仅优于先前算法，改进值等于 1.17 倍。总体结果表明，所提出的算法在网格系统中是有效的，另外四位足以提高作业调度系统的性能。平均结果表明，依赖作业调度（DJS）算法在总执行时间和平均等待时间方面优于之前的算法，改进值分别为 1.18 和 1.92 倍。而带有加权因子的 DJS 算法（DJSJP）在总执行时间上仅优于先前算法，改进值等于 1.17 倍。总体结果表明，所提出的算法在网格系统中是有效的，另外四位足以提高作业调度系统的性能。平均结果表明，依赖作业调度（DJS）算法在总执行时间和平均等待时间方面优于之前的算法，改进值分别为 1.18 和 1.92 倍。而带有加权因子的 DJS 算法（DJSJP）在总执行时间上仅优于先前算法，改进值等于 1.17 倍。总体结果表明，所提出的算法在网格系统中是有效的，另外四位足以提高作业调度系统的性能。而带权重因子的 DJS 算法（DJSJP）在总执行时间上仅优于之前的算法，改进值仅为 1.17 倍。总体结果表明，所提出的算法在网格系统中是有效的，另外四位足以提高作业调度系统的性能。而带有加权因子的 DJS 算法（DJSJP）在总执行时间上仅优于先前算法，改进值等于 1.17 倍。总体结果表明，所提出的算法在网格系统中是有效的，另外四位足以提高作业调度系统的性能。