DocumentCode :
3091444
Title :
Adaptive policy trigger mechanism for OBSS
Author :
Feng, Dan ; Zeng, Lingfang ; Wang, Fang ; Qin, Lingjun ; Liu, Qun
Author_Institution :
Key Lab. of Data Storage Syst., Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
2
fYear :
2005
fDate :
28-30 March 2005
Firstpage :
591
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.
Keywords :
learning (artificial intelligence); object-oriented methods; storage area networks; storage management; NAS; OBSS; SAN; adaptive policy trigger mechanism; block-based storage devices; data block management; data distribution; machine learning; mass storage system self-management; object attributes; object methods; object-based storage system; Application software; Computer science education; Data storage systems; Databases; Educational technology; Hardware; Intelligent systems; Laboratories; Scalability; Storage area networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Information Networking and Applications, 2005. AINA 2005. 19th International Conference on
ISSN :
1550-445X
Print_ISBN :
0-7695-2249-1
Type :
conf
DOI :
10.1109/AINA.2005.76
Filename :
1423759
Link To Document :
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