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Popularity and correlation aware data replication strategy based on half-life concept and clustering in cloud system

机译:基于半衰期概念和云系统聚类的流行和相关意识数据复制策略

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In the new millennium, a myriad of large-scale applications (e.g., social networks, ecommerce, internet of things, and scientific experiments) often generate large volumes of data. Given their volumes, their heterogeneous and distributed nature, the management of such data constitutes a challenge for distributed systems, particularly cloud computing. In this regard, data replication is a well-known and effective data management technique that consists in creating multiple copies of the same data in different storage resources. In this article, we propose a popularity and correlation based data replication strategy, called PCDR. The main idea of our strategy is to replicate a set of the most popular correlated file groups based on files access history analysis. In this respect, the popularity of the files in each group is determined while taking into consideration temporal locality. Moreover, a clustering technique is used to find groups of correlated files. Using the CloudSim simulator, extensive experimentations show that our proposed strategy outperforms other strategies for several evaluation metrics.
机译:在新的千年内,无数的大规模应用程序(例如,社交网络,电子商务,事物和科学实验)经常产生大量数据。鉴于其卷,其异构和分布式性质,这些数据的管理构成了分布式系统,特别是云计算的挑战。在这方面,数据复制是一种众所周知的和有效的数据管理技术,包括在不同存储资源中创建相同数据的多个副本。在本文中,我们提出了一种被称为PCDR的基于流行度和相关的数据复制策略。我们的策略的主要思想是根据文件访问历史分析复制一组最受欢迎的相关文件组。在这方面,在考虑时间位置时确定每个组中文件的普及。此外,聚类技术用于查找相关文件组。使用CloudSim模拟器,广泛的实验表明,我们所提出的策略优于几种评估指标的其他策略。

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