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EFFICIENT GRID SCHEDULING THROUGH THE INCREMENTAL SCHEDULE-BASED APPROACH

机译:通过基于增量计划的方法进行有效的网格计划

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Although Grid users demand good performance for their jobs, this requirement is often not satisfied by the widely used queue-based scheduling approaches. This article concentrates on the application of schedule-based methods that improve on both the service delivered to the user and the traditional objective of machine usage. Importantly, the interaction between the incremental application of these methods and the dynamic character of the problem allows reasonable runtimes to be achieved. Two new schedule-based methods that are designed to schedule dynamically arriving jobs on machines in a computational Grid are formally described in the article. The Earliest Gap-Earlier Deadline First (EG-EDF) policy fills the earliest gap in the known schedule with newly arriving jobs, incrementally building a new schedule. If the gap is not suitable for an incoming job, the EDF policy is used to modify the existing schedule. A Tabu search algorithm is used to further optimize the schedule by moving selected jobs into the earliest suitable gaps. The proposed incremental schedule-based methods are compared with some of the most common queue-based scheduling algorithms such as FCFS (First Come First Served), EASY backfilling (Extensible Argonne Scheduler sYstem), Flexible backfilling as well as with the nonincremental version of the EG-EDF schedule-based policy.
机译:尽管网格用户要求其工作具有良好的性能,但是,广泛使用的基于队列的调度方法通常无法满足此要求。本文重点介绍基于计划的方法的应用,这些方法既可以改善向用户提供的服务,又可以改善传统的机器使用目标。重要的是,这些方法的增量应用程序与问题的动态特征之间的交互作用可以实现合理的运行时间。本文正式介绍了两种新的基于调度的方法,这些方法旨在调度计算网格中计算机上的动态到达作业。最早的差距-较早的截止日期优先(EG-EDF)政策用新到的工作填补了已知时间表中的最早差距,并逐步建立了新时间表。如果该间隔不适合传入作业,则使用EDF策略修改现有计划。禁忌搜索算法用于通过将选定的作业移入最早的合适间隔来进一步优化计划。提议的基于增量调度的方法与一些最常见的基于队列的调度算法进行了比较,例如FCFS(先到先服务),EASY回填(可扩展Argonne调度程序系统),灵活回填以及非增量版本的EG-EDF基于计划的策略。

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