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Dynamic file replica location and selection strategy in data grids

机译:数据网格中的动态文件副本位置和选择策略

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摘要

In this paper, we present the design of PU-DG optimizer toolbox (also known as PU-DG Optibox), which not only finds out the best strategy according to huge amount of simulation results but also proposes the min-max balancing workload method to upgrade the efficiency of execution in data grid environments. Data grid is one of key factors to build up large-scale dataset storage system and providing high performance computing capacity, by connecting scattered computing and storage resources located dispersedly in the grid. One major challenge in data grids is how to provide good and timely access to huge amount of data in distributed locations, given the high latency of interconnection networks. In this paper, we present the design framework of PU-DG Optibox for data grid environments. The proposed toolbox is a package containing a number of high-end techniques and methods running as middleware on top of data grid platforms, in order to optimize file downloads, by improving its efficiency and performance. The PU-DG Optibox provides users and developers possibilities for setting their own priority strategies. In addition, min-max balancing workload method is proposed to avoid that one computing node with lower network bandwidth to receive a job that has high complexity of job factor. Experimental results of techniques packaged in the proposed toolbox demonstrate its effectiveness.
机译:在本文中,我们介绍了PU-DG优化工具箱(也称为PU-DG Optibox)的设计,这不仅根据大量的仿真结果找到了最佳策略,还提出了最小的均衡工作负载方法升级数据网格环境中的执行效率。数据网格是构建大规模数据集存储系统并提供高性能计算能力的关键因素之一,通过连接分散在网格中的分散的计算和存储资源。考虑到互连网络的高延迟,数据网格中的一个主要挑战是如何提供良好的,并及时访问分布式位置中的大量数据。在本文中,我们介绍了PU-DG Optibox的设计框架进行数据网格环境。所提出的工具箱是包含许多在数据网格平台上运行作为中间件的高端技术和方法的包,以便通过提高其效率和性能来优化文件下载。 PU-DG Optibox为用户和开发人员提供了设置自己的优先级策略的可能性。此外,提出了最小的最大平衡工作负载方法,以避免具有较低网络带宽的一个计算节点以接收具有高复杂性的作业因子的作业。拟议工具箱中包装的技术的实验结果表明了其有效性。

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