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Agent Based Priority Heuristic for Job Scheduling on Computational Grids

机译:计算网格上基于Agent的优先级启发式作业调度

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A grid is an infrastructure for resource sharing. At present, many scientific applications require high computing power in processing, which can only be achieved by using the computational grid. For the selection and allocation of grid resources to current and future applications, grid job scheduling is playing a very vital role for computational grids. They constitute the building blocks for making grids available to the society. The efficient and effective scheduling policies, when assigning different jobs to specific resources, are very important for a grid to process high computing intensive applications. This paper presents an agent based job scheduling algorithm for efficient and effective execution of user jobs. This paper also includes the comparative performance analysis of our proposed job scheduling algorithm along with other well known job scheduling algorithms considering the quality of service parameters like waiting time, turnaround time, response time, total completion time, bounded slowdown time and stretch time. We also conducted the QoS based evaluation of the scheduling algorithms on an experimental computational grid using real workload traces. Experimental evaluation confirmed that the proposed grid scheduling algorithms posses a high degree of optimality in performance, efficiency and scalability. This paper also includes a statistical analysis of real workload traces to present the nature and behavior of jobs.
机译:网格是资源共享的基础架构。当前,许多科学应用需要处理中的高计算能力,这只能通过使用计算网格来实现。为了选择网格资源并将其分配给当前和将来的应用程序,网格作业调度对于计算网格起着至关重要的作用。它们构成了为社会提供网格的基础。将不同的作业分配给特定资源时,高效而有效的调度策略对于网格处理高计算密集型应用程序非常重要。本文提出了一种基于代理的作业调度算法,可以高效,有效地执行用户作业。本文还包括对我们提出的作业调度算法以及其他众所周知的作业调度算法的比较性能分析,其中考虑了服务质量参数,例如等待时间,周转时间,响应时间,总完成时间,有限制的减速时间和伸展时间。我们还使用真实的工作量跟踪在实验计算网格上对调度算法进行了基于QoS的评估。实验评估证实,提出的网格调度算法在性能,效率和可伸缩性方面具有高度的最优性。本文还包括对实际工作量跟踪的统计分析,以显示工作的性质和行为。

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