Suchit A. Sapate

Work place: Persistent Systems Ltd., Nagpur, 440022, India

E-mail: suchit.sapate2005@gmail.com

Website:

Research Interests: Program Analysis and Transformation, Data Structures and Algorithms, Data Mining

Biography

Suchit A. Sapate pursed Bachelor of Engineering in Computer engineering department from University of Nagpur, India in 2008 and Master of Technology in Computer Science & engineering department from University of Nagpur, India in 2015. He is currently working as Project Lead in Persistent Systems Ltd. since 2008. His main research work focuses on Data Analytics and Data Mining. He has published 3 papers in reputed international journal.

Author Articles
Effective XML Compressor: XMill with LZMA Data Compression

By Suchit A. Sapate

DOI: https://doi.org/10.5815/ijeme.2019.04.01, Pub. Date: 8 Jul. 2019

The XMill is an efficient XML compression tool which takes the advantage of awareness of XML. XMill compresses the data on the basis of three principles- separate the XML structure from the data, group related data and apply the semantic compressors. The XMill uses the gZip library to compress the XML string data for increasing the compression ratio. Here we have proposed a new method to increase the compression ratio of XMill tool. In this method we have added the 7Zip library to the XMill tool; 7Zip library uses the LZMA algorithm to compress the data. LZMA is an enhanced & improved version of LZ77 algorithm which is used in the gZip library. LZMA algorithm has following features over the LZ77 algorithm

•Uses up to 4GB dictionary length instead of 32KB for removing the duplicate data.
•Uses the look-a-head approach instead of greedy approach.

•Uses the optimal parsing, shorter code for recently repeated matches.
•Uses the context handling.
Due to the above features our proposed approach achieves the best compression ratio with a comparable compression speed.

[...] Read more.
Other Articles