IaaS云环境下增强的存储管理优化

A. Devarajan, T. Sudalaimuthu, K. Sankaran
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引用次数: 0

摘要

云计算是与IaaS相关的不可避免的重大发展。由于数据分布和数据存储在IaaS服务中的升级,存储空间日益增加。云计算有很多好处,比如可伸缩性、可访问性、节省成本,几乎所有行业都对将数据转移到云存储感兴趣。使用这种IaaS服务,必须了解与数据存储管理功能以及跨众多客户的分布相关的最大挑战。这也会影响与带宽利用率相关的性能和用户体验。本文提出了一种消除重复数据的存储管理优化(SMO)方法,以节省存储空间,提高网络存储速度和带宽利用率。结构良好的元数据用于识别相应数据元素上的重复。元数据原型的评估有助于分析用户的文件访问模式,并根据频繁可访问性排序系统确定未来的访问预测。SMO系统生成一个仪表板,其中包含与应用程序数据文件和访问详细信息相关的详细信息。在仿真平台上使用所提出的系统SMO实现,可以显示出比正常系统高达11.85%的空间优化,并且带宽的可访问性增加了近84%。
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Enhanced Storage Management Optimization in IaaS Cloud Environment
Cloud computing is unavoidable significant development that utilizes progressive related to IaaS. The storage is increasing day by day due to upgrades in data distribution and data storing in IaaS services. Having lot of benefit of cloud such as scalability, accessibility, cost saving, almost all industry is interested in shifting their data to cloud storage. With this IaaS services, it is essential to know the biggest challenge related to the data storage management capabilities and also distribution across numerous customer. This also has impact on performance and user experience related to the bandwidth utilization. In this paper the proposed Storage Management Optimization (SMO) eliminates duplicate data to save storage space and increase bandwidth utilization with respect to storage speed of network. The well-structured metadata is used to identify duplication on the corresponding data elements. Evaluation of a metadata prototype helps to analyze the file access patterns of user and to determine the future access prediction in terms of frequent accessibility ranking system. The SMO system generates a dashboard having details related to application data files and access details. Implementation using the proposed system SMO in simulation platform can show space optimization upto 11.85% than the normal system and bandwidth increases with respect to accessibility at the rate almost 84%.
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