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Title:      FAST FLASH MEMORY CACHING BASED ON FILE ACCESS FREQUENCY
Author(s):      Chenhan Liao , Frank Wang , Na Helian , Sining Wu , Yuhui Deng
ISBN:      ISSN: 1646-3692
Editors:      Pedro Isaías and Marcin Paprzycki
Year:      2009
Edition:      V IV,2
Keywords:      Storage system, Access Frequency, Prediction, KDD
Type:      Journal Paper
First Page:      28
Last Page:      40
Language:      English
Cover:      no-img_eng.gif          
Full Contents:      click to dowload Download
Paper Abstract:      In modern file systems, traces monitor the file operations and user behaviors. Inevitably, large amount of data continuously produced in daily manner. We show that the knowledge hidden behind system traces can help us understand the system and user behaviors. In this paper, we illustrate that once a file is created with a set of attributes, such as name, type, permission mode, owner and owner group, its future access frequency is predictable. A decision-tree-based predictive model is established to predict whether a file will be frequently accessed or not. By consulting with the rules generated from the predictive model over diverse real-system NFS traces, the model can predict a newly created file’s future access frequency with sufficient accuracy. We further introduce an evolutionary storage system, which employs the predicted frequency information to decide what files to keep in a fast storage device, flash memory. The trace-driven experimental results indicate that the performance speedup due to the predictionenabled optimization is 2-4 compared with base case.
   

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