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Content Provider | IEEE Xplore Digital Library |
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Author | Weiling Chang Xiaochun Yun Binxing Fang Shupeng Wang Xiangzhan Yu |
Copyright Year | 2010 |
Description | Author affiliation: Research Centre of Computer Network and Information Security Technology, Harbin Institute of Technology, Harbin 150001, China (Weiling Chang; Binxing Fang; Xiangzhan Yu) || Institute of Computing Technology, Chinese Academy of Science, Beijing 100080, China (Xiaochun Yun; Shupeng Wang) |
Abstract | The mainstream compression algorithms, such as LZ, Huffman, PPM etc., have been extensively studied in recent years. However, rather less attention has been paid to the block algorithm of those algorithms. The aim of this study was therefore to investigate the block LZSS. We studied the relationship between the compression ratio of block LZSS and the value of index or length. We found that the bit of length has little effect on the compression performance of block LZSS, and the bit of index has a significant effect on the compression ratio. Results of the experiment show that to obtain better efficiency from block LZSS, a moderate sized block which is greater than 32KiB, may be optimal, and the optimal block size does not depend on file types. We also investigated factors which affect the optimal block size. We found that good data locality implies a large skew in the data distribution, and the greater data distribution skew, the better the compression ratio. |
File Size | 2807439 |
File Format | |
ISBN | 9781424458219 |
e-ISBN | 9781424458240 |
DOI | 10.1109/ICFCC.2010.5497477 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2010-05-21 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Lempel-Ziv-Storer-Szymanski Codecs block LZSS Data compression Entropy Compression algorithms File systems Information security Bandwidth Propagation losses Computer networks Huffman coding lossless data compression |
Content Type | Text |
Resource Type | Article |
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