英语（全英文）architecture design of global distributed storage system for data grid 本科论文.doc

Architecture Design of Global Distributed Storage System for Data Grid Longbo Ran, Hai Jin, Zhiping Wang, Chen Huang, Yong Chen, and Yongjie Jia Internet and Cluster Computing Center Huazhong University of Science and Technology, Wuhan 430074, China Email: hjin@ Abstract Data grids are becoming increasingly important for sharing large data collections, archiving and disseminating. In this paper we describe architecture of global distributed storage system for data grid. We focus on the management and the capability for the maximum users and maximum resources on the Internet, as well as performance and other issues. Keywords: Data grids, Match tree, Metadata, Name space Introduction Data-intensive, high-performance computing applications require the efficient management and transfer of terabytes or petabytes of information in wide-area, distributed computing environments [1][28]. Examples of data-intensive applications include experimental analyses and simulations in several scientific disciplines, such as high-energy physics, climate modeling, earthquake engineering and astronomy [2][3]. These applications share several requirements. Massive data sets must be shared by a large community of hundreds or thousands of users distributed around the world. Data grids are becoming increasingly important for sharing large data collections, archiving and disseminating. Researches on massive storage system have gained significant achievements. There are already a number of storage systems used by the grid community, each of which was designed to satisfy specific needs and requirements for storing, transferring and accessing large datasets. These include Distributed Parallel Storage System (DPSS) and High Performance Storage System (HPSS), which provide high performance access to data and utilize parallel data transfer and/or striping across multiple servers to improve performance [4][28]. Distributed File System (DFS) supports high-volume usage, dataset replication