College of Information Science and Technology / Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Hunan Agricultural University, Changsha, China.
School of Information Science and Engineering, Hunan University, Changsha, China.
PLoS One. 2018 Nov 20;13(11):e0207596. doi: 10.1371/journal.pone.0207596. eCollection 2018.
Recently, computational Grids have proven to be a good solution for processing large-scale, computation intensive problems. However, the heterogeneity, dynamics of resources and diversity of applications requirements have always been important factors affecting their performance. In response to these challenges, this work first builds a Grid job scheduling architecture that can dynamically monitor Grid computing center resources and make corresponding scheduling decisions. Second, a Grid job model is proposed to describe the application requirements. Third, this paper studies the characteristics of commercial interconnection networks used in Grids and forecast job transmission time. Fourth, this paper proposes an application-aware job scheduling mechanism (AJSM) that includes periodic scheduling flow and a heuristic application-aware deadline constraint job scheduling algorithm. The rigorous performance evaluation results clearly demonstrate that the proposed application-aware job scheduling mechanism can successful schedule more Grid jobs than the existing algorithms. For successful scheduled jobs, our proposed AJSM method is the best algorithm for job average processing time and makespan.
最近，计算网格已被证明是处理大规模、计算密集型问题的一种很好的解决方案。然而，资源的异构性、动态性和应用程序需求的多样性一直是影响其性能的重要因素。针对这些挑战，本工作首先构建了一个可以动态监测网格计算中心资源并做出相应调度决策的网格作业调度架构。其次，提出了一种网格作业模型来描述应用程序需求。第三，本文研究了网格中使用的商业互联网络的特点，并预测了作业传输时间。第四，提出了一种面向应用的作业调度机制（AJSM），包括周期性调度流程和启发式面向应用的截止日期约束作业调度算法。严格的性能评估结果清楚地表明，所提出的面向应用的作业调度机制可以成功调度比现有算法更多的网格作业。对于成功调度的作业，我们提出的 AJSM 方法是作业平均处理时间和完成时间的最佳算法。
