พร พันธุ์จงหาญ. File Type Classification for Adaptive Object File System. Master's Degree(Computer Engineering). King Mongkut's University of Technology Thonburi. : King Mongkut's University of Technology Thonburi, 2006.
File Type Classification for Adaptive Object File System
Abstract:
This thesis gives an overview of a novel storage management concept, called Adaptive Object File System (AOFS).
The design of the file type classification module in AOFS is emphasized. The module attempts to increase the efficiency
through the dynamic tuning technique, which automatically classifies files using attributes and access pattern. The file
classification, thus, allows files to be stored in the most efficient way. The key idea is to utilize the file properties, such
as access pattern and size to select adaptive file system policies (e.g. disk allocation, redundancy, and caching strategies).
Moreover, a metadata store is maintained to provide the best possible dynamic tuning strategy for any given operating
period. The static classification design is done based on file type identification, while the dynamic classification adapts
the Markov chains model for prediction. The main goal of the AOFS design is to enhance the system performance,
the storage efficiency and flexibility.