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19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers) (2005)
Taipei, Taiwan
Mar. 25, 2005 to Mar. 30, 2005
ISSN: 1550-445X
ISBN: 0-7695-2249-1
pp: 591-595
Dan Feng , Huazhong University of Science and Technology
Lingfang Zeng , Huazhong University of Science and Technology
Fang Wang , Huazhong University of Science and Technology
Lingjun Qin , Huazhong University of Science and Technology
Qun Liu , Huazhong University of Science and Technology
ABSTRACT
Traditional storage systems, such as NAS, SAN, are largely unaware of the users and applications actually using the storage, because block-based storage devices manage opaque data blocks. But, with OBSS (object-based storage system), the attributes and methods among the storage devices can be adopted in the storage system, the data can be distributed on some of the storage devices and organized better to anticipate users demand. In this paper, the scalability of object storage (including object attributes, object methods and OBSS) is studied. And a self-managing approach, denoted adaptive policy trigger mechanism (APTM), is presented. APTM borrows proven machine learning techniques and takes the perspective scalable object storage. The implementation reveals that APTM is the embodiment of the idea about smart storage device and facilitates to self-manage mass storage system.
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CITATION

L. Qin, Q. Liu, L. Zeng, F. Wang and D. Feng, "Adaptive Policy Trigger Mechanism for OBSS," 19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers)(AINA), Taipei, Taiwan, 2005, pp. 591-595.
doi:10.1109/AINA.2005.76
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