Paper Info
Title
Performance optimization of small file i/o with adaptive migration strategy in cluster file system
Abstract
While cluster file systems exploit data striping scheme to boost large file I/O throughput, small file performance is impaired and neglected. Common metadata-based optimizations introduce obstacles such as metadata server overload and migration latency. In this paper, a novel adaptive migration strategy is incorporated into metadata-based optimization to alleviate these side effects by migrating file dynamically. Guided by proposed adaptive migration threshold model, two types of file migration are applied to reduce metadata server load without degrading current performance of file system obviously. Schemes of latency hiding and migration consistency are also introduced to reduce overhead induced by small file optimization. Our results indicate that proposed optimization can substantially improve file creation and deletion performance, and boost small file I/O throughput by more than 20%. Moreover, side effects on overall performance produced by file migration are slight and can be absorbed by improvements.
Year
DOI
Venue
2009
10.1007/978-3-642-11842-5_33
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Keywords
Field
DocType
file system,small file optimization,large file,file migration,migrating file dynamically,small file performance,performance optimization,small file i,adaptive migration strategy,cluster file system,file creation,o throughput,small file,threshold model,side effect
Distributed File System,Metadata,File system,Self-certifying File System,Computer science,Device file,Parallel computing,Input/output,Throughput,File system fragmentation,Distributed computing
Conference
Volume
Issue
ISSN
5938 LNCS
null
16113349
ISBN
Citations 
PageRank 
3-642-11841-0
2
0.38
References 
Authors
6
4
Name
Order
Citations
PageRank
Xiuqiao Li1515.74
Bin Dong2252.50
Limin Xiao310728.51
Li Ruan412325.10