Open Access System for Information Sharing

Login Library

 

Article
Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Enhancing prediction accuracy in PCM-based file prefetch by constained pattern replacement algorithm SCIE SCOPUS

Title
Enhancing prediction accuracy in PCM-based file prefetch by constained pattern replacement algorithm
Authors
Choi, IPark, C
Date Issued
2003-01
Publisher
SPRINGER-VERLAG BERLIN
Abstract
In modern file systems, I/O latency is still major bottleneck of performance and predictive file prefetching is one of promising approaches that can enhance I/O performance of file system. To utilize predictive file prefetching to file system, there should be a file access pattern prediction model that can predict future file access. Partitioned Context Model(PCM) [2] is known as one of the most accurate file access pattern prediction models[3]. In order to predict longer sequence, the order of PCM must be increased. However, the prediction accuracy of PCM decreases when PCM is in high order. Careful analysis reveals that the pattern replacement algorithm in the PCM is the major cause in decay of the prediction accuracy. The pattern replacement algorithm destroys file access patterns without successful training of newly occurred file access patterns. We proposed the constrained pattern replacement algorithm to overcome this adverse effect by revising replacement condition. The simulation results using the DFSTrace system trace[13] show that the proposed algorithm improves prediction accuracy without any extra cost by 3.5% compared to traditional pattern replacement algorithm of PCM(about 40% of the accuracy bound of 7%).
URI
https://oasis.postech.ac.kr/handle/2014.oak/18392
DOI
10.1007/3-540-44864-0_22
ISSN
0302-9743
Article Type
Article
Citation
LECTURE NOTES IN COMPUTER SCIENCE, vol. 2660, page. 213 - 222, 2003-01
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

박찬익PARK, CHAN IK
Dept of Computer Science & Enginrg
Read more

Views & Downloads

Browse