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首页> 外文期刊>Journal of Parallel and Distributed Computing >A path selection-based algorithm for real-time data staging in Grid applications
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A path selection-based algorithm for real-time data staging in Grid applications

机译：Grid应用程序中基于路径选择的实时数据分级算法

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摘要

Efficient data scheduling is becoming an important issue in distributed real-time applications that produce huge data sets. The Grid environment on which these applications may run seeks to harness the geographically distributed resources for the applications. Scheduling components should account for real-time measures of the applications and reduce communication overhead due to enormous data size experienced, especially in dissemination applications. In this study, we consider the data staging scheme to provide the dissemination of large-scale data sets for the distributed real-time applications. We propose a new path selection-based algorithm for optimizing a criterion that reflects the general satisfiability of the system. The algorithm adopts a blocking-time analysis method combined with a simple heuristic to explore the most likely regions of a search space. Two heuristics are provided for the algorithm to explore these regions of the search space. Simulation results show that the proposed algorithm together with either of the heuristic has higher performance compared to other algorithms in the literature. We also show by simulation that a new optimization criterion we proposed in this study is successful in improving the performance of the individual applications.
机译：在产生大量数据集的分布式实时应用程序中，有效的数据调度已成为重要的问题。这些应用程序可以在其上运行的Grid环境试图为应用程序利用地理上分散的资源。调度组件应考虑应用程序的实时度量，并由于经历的巨大数据量（尤其是在分发应用程序中）而减少通信开销。在这项研究中，我们考虑使用数据分段方案为分布式实时应用程序提供大规模数据集的分发。我们提出了一种基于路径选择的新算法，用于优化反映系统总体满意度的标准。该算法采用阻塞时间分析方法，结合简单的启发式方法来探索搜索空间中最可能的区域。为该算法提供了两种启发式方法，以探索搜索空间的这些区域。仿真结果表明，与文献中的其他算法相比，该算法与两种启发式算法都具有较高的性能。我们还通过仿真表明，我们在这项研究中提出的新的优化标准可以成功地提高单个应用程序的性能。

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