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Autonomic data management system in grid environment

机译:网格环境中的自主数据管理系统

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摘要

In grid environment, a job may execute on a node that is geographically far away from its data files. These files are stored in heterogeneous storage systems located at geographically distributed virtual organizations. The current approach includes explicit data file transfers to execution nodes, which forces users to deal with different administrative policies at each site and various data access mechanisms on each storage system. This implies a lot of human interventions in order to develop dedicated programs and scripts for data transfers for job execution. We have developed a framework, called GRAVY, which enables transparent data access between distributed file systems irrespective of their heterogeneity. This feature enables high-level schedulers integrated with GRAVY to control data placements like computational jobs (i.e., they can be queued, scheduled and monitored). In particular, GRAVY provides reliable and efficient data placement across multiple protocols and has a mechanism for transfer failure recovery without any human interaction.
机译:在网格环境中,作业可能在地理位置上远离其数据文件的节点上执行。这些文件存储在位于地理位置分散的虚拟组织中的异构存储系统中。当前方法包括将数据文件显式传输到执行节点,这迫使用户应对每个站点上的不同管理策略以及每个存储系统上的各种数据访问机制。这意味着需要大量的人工干预,以便开发专用程序和脚本来进行数据传输以执行作业。我们已经开发了一个名为GRAVY的框架,该框架可实现分布式文件系统之间的透明数据访问,而不论其异构性如何。此功能使与GRAVY集成的高级调度程序可以控制数据位置,例如计算作业(即,可以对它们进行排队,调度和监视)。尤其是,GRAVY可跨多种协议提供可靠而有效的数据放置,并具有无需任何人工干预即可恢复传输故障的机制。

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