Improving the performance of log-structured file systems with adaptive block rearrangement

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Improving the performance of log-structured file systems with adaptive block rearrangement

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Symposium on Applied Computing archive
Proceedings of the 2007 ACM symposium on Applied computing table of contents

Seoul, Korea

SESSION: Operating systems and adaptive applications table of contents

Pages: 1136 - 1140

Year of Publication: 2007

ISBN:1-59593-480-4

Authors

Mei-Ling Chiang	National Chi-Nan University, Puli, Taiwan, R.O.C.
Jia-Shin Huang	National Chi-Nan University, Puli, Taiwan, R.O.C.

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 6, Downloads (12 Months): 49, Citation Count: 1

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ABSTRACT

Log-Structured File System (LFS) is famous for its optimization for write performance. Because of its append-only nature, garbage collection is needed to reclaim the space occupied by the obsolete data. The cleaning overhead could significantly decrease the performance of file system. However, traditional cleaning policies do not consider the storage location where the valid data in the cleaned segments should be placed and rewritten to. In this paper, we propose a new method called R-LFS to dynamically reorganize data in disk to approximate the organ pipe heuristic that can place data in disk optimally. Basically, frequently accessed data are dynamically clustered and placed toward the center of disk, whereas less accessed data are moved and placed toward the edges of disk to reduce disk seek time. The essence of R-LFS is that R-LFS takes advantage of the chance of data reorganization during segment cleaning and data writing, no extra overhead is incurred for this data reorganization. Besides, because hot data and cold data are in nature separately clustered under R-LFS, cleaning overhead can be substantially reduced as well. Performance evaluation under both trace-driven simulation and practical implementation on NetBSD/LFS shows that R-LFS can effectively improve the performance of LFS.

REFERENCES

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	1	Sedat Akyürek , Kenneth Salem, Adaptive block rearrangement under UNIX, Software—Practice & Experience, v.27 n.1, p.1-23, Jan. 1997 [doi>10.1002/(SICI)1097-024X(199701)27:1<1::AID-SPE66>3.3.CO;2-A]
	2	Trevor Blackwell , Jeffrey Harris , Margo Seltzer, Heuristic cleaning algorithms in log-structured file systems, Proceedings of the USENIX 1995 Technical Conference Proceedings on USENIX 1995 Technical Conference Proceedings, p.23-23, January 16-20, 1995, New Orleans, Louisiana
	3	Mei-Ling Chiang , Paul C. H. Lee , Ruei-Chuan Chang, Using data clustering to improve cleaning performance for plash memory, Software—Practice & Experience, v.29 n.3, p.267-290, March 1999 [doi>10.1002/(SICI)1097-024X(199903)29:3<267::AID-SPE233>3.0.CO;2-T]
	4	M.-L. Chiang , R.-C. Chang, Cleaning policies in mobile computers using flash memory, Journal of Systems and Software, v.48 n.3, p.213-231, Nov. 1, 1999 [doi>10.1016/S0164-1212(99)00059-X]
	5	David D. Grossman , Harvey F. Silverman, Placement of Records on a Secondary Storage Device to Minimize Access Time, Journal of the ACM (JACM), v.20 n.3, p.429-438, July 1973 [doi>10.1145/321765.321775]
	6	Jeanna Neefe Matthews , Drew Roselli , Adam M. Costello , Randolph Y. Wang , Thomas E. Anderson, Improving the performance of log-structured file systems with adaptive methods, Proceedings of the sixteenth ACM symposium on Operating systems principles, p.238-251, October 05-08, 1997, Saint Malo, France [doi>10.1145/268998.266700]
	7	NetBSD Project, http://www.netbsd.org.
	8	Mendel Rosenblum , John K. Ousterhout, The design and implementation of a log-structured file system, ACM Transactions on Computer Systems (TOCS), v.10 n.1, p.26-52, Feb. 1992 [doi>10.1145/146941.146943]
	9	C. Ruemmler and J. Wilkes, "UNIX Disk Access Patterns," Proceedings of the 1993 Winter USENIX, pp. 405--420, 1993.
	10	S. D. Carson, A system for adaptive disk rearrangement, Software—Practice & Experience, v.20 n.3, p.225-242, March 1990 [doi>10.1002/spe.4380200302]
	11	Jun Wang , Yiming Hu, WOLF - A Novel Reordering Write Buffer to Boost the Performance of Log-Structured File Systems, Proceedings of the Conference on File and Storage Technologies, p.47-60, January 28-30, 2002
	12	Wenguang Wang , Yanping Zhao , Rick Bunt, HyLog: A High Performance Approach to Managing Disk Layout, Proceedings of the 3rd USENIX Conference on File and Storage Technologies, March 31-31, 2004, San Francisco, CA
	13	John Wilkes , Richard Golding , Carl Staelin , Tim Sullivan, The HP AutoRAID hierarchical storage system, ACM Transactions on Computer Systems (TOCS), v.14 n.1, p.108-136, Feb. 1996 [doi>10.1145/225535.225539]
	14	C. K. Wong, Minimizing Expected Head Movement in One-Dimensional and Two-Dimensional Mass Storage Systems, ACM Computing Surveys (CSUR), v.12 n.2, p.167-178, June 1980 [doi>10.1145/356810.356814]