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Virtualization of Large-Scale Data Storage System to Achieve Dynamicity and Scalability in Grid Computing

机译:大型数据存储系统的虚拟化以实现网格计算的动态性和可伸缩性

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Data storage management is one of the most challenging issues for Grid resource management since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance dedicated servers are used for data storage and data replication. This allows opportunistic grids to share not only the computational cycles, but also the storage space. This paper explains new mechanism for Dynamic and Scalable Storage Management (DSSM) in grid environments is proposed. The storage can be transparently accessed from any grid machine, allowing easy data sharing among grid users and applications. The concept of virtual ids that, allows the creation of virtual spaces has been introduced and used. The DSSM divides all Grid Oriented Storage devices (nodes) into multiple geographically distributed domains and to facilitate the locality and simplify the intra-domain storage management. Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows. To this end, we propose four axes that define: DSSM architecture and algorithms description, Storage resources and resource discovery into Grid service, Evaluate purpose prototype system, dynamically, scalability, and bandwidth, and Discuss results. Algorithms at bottom and upper level for standardization dynamic and scalable storage management, along with higher bandwidths have been designed.
机译:数据存储管理是网格资源管理中最具挑战性的问题之一,因为大量的数据密集型应用程序经常涉及高度的数据访问局部性。网格应用程序通常处理大量数据。在传统方法中,高性能专用服务器用于数据存储和数据复制。这使得机会网格不仅可以共享计算周期,还可以共享存储空间。本文介绍了网格环境中动态和可扩展存储管理(DSSM)的新机制。可以从任何网格机器透明地访问该存储,从而允许在网格用户和应用程序之间轻松共享数据。引入并使用了允许创建虚拟空间的虚拟ID概念。 DSSM将所有面向网格的存储设备(节点)划分为多个地理上分散的域,以便于本地化并简化域内存储管理。随着需求的增长,采用了基于网格服务的存储资源来逐个堆叠简单的模块化服务。为此,我们提出了四个定义的轴:DSSM体系结构和算法描述,存储资源和网格服务中的资源发现,评估目的原型系统,动态,可伸缩性和带宽,以及讨论结果。已设计了用于底层动态和可扩展存储管理以及更高带宽的底层和高层算法。

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