The International Arab Journal of Information Technology (IAJIT)

..............................
..............................
..............................


A New Way of Accelerating Web by Compressing Data with Back Reference-Prefer Geflochtener

This research focused on the synthesis of an iterative approach to improve speed of the web and also learning the new methodology to compress the large data with enhanced backward reference preference. In addition, observations on the outcomes obtained from experimentation, group-benchmarks compressions, and time splays for transmissions, the proposed system have been analysed. This resulted in improving the compression of textual data in the Web pages and with this it also gains an interest in hardening the cryptanalysis of the data by maximum reducing the redundancies. This removes unnecessary redundancies with 70% efficiency and compress pages with the 23.75-35% compression ratio.

 


[1] Arya G., Singh A., Painuly R., Bhadri S., and Maurya S., “LZ squeezer A Compression Technique based on LZ77 and LZ78,” The SIJ Transactions on Computer Science Engineering and its Applications, vol. 1, no. 1, pp. 29- 32, 2013.

[2] Akman I., Bayindir H., Ozleme S., Akin Z., and Misra S., “Lossless Text Compression Technique Using Syllable Based Morphology,” The International Arab Journal of Information Technology, vol. 8, no. 1, pp. 66-74, 2011.

[3] Awan F. and Mukherjee A., “LIPT: A Lossless Text Transform to Improve Compression,” in Proceeding of International Conference on Information Technology: Coding and Computing, Las Vegas, pp. 452-460, 2001.

[4] Burrows M. and Wheeler D., A Block-Sorting Lossless Data Compression Algorithm, Digital Systems Research Centre, 1994.

[5] Calgary corpus, http://www.data- compression.info/Corpora/CalgaryCorpus/index. htm, Last Visited 2014.

[6] Vandevenne L., http://googledevelopers.blogspot.in/2013/02/com press-data-more-densely-with-zopfli.html Googledevelopers.blogspot.com, Last Visited 2014.

[7] Canterbury Corpus., http://corpus.canterbury.ac.nz/resources/cantrbry .zip, Last Visited 2014.

[8] Data Compression the Dictionary Way, http://www.i-programmer.info/babbages- bag/515-data-compression-the-dictionary- way.html?start=1, Last Visited 2014.

[9] Enwik8 Corpus, http://mattmahoney.net/dc/enwik8.zip, Last Visited 2014. A New Way of Accelerating Web by Compressing Data with Back Reference-Prefer Geflochtener 447

[10] Fielding R., Gettys J., Mogul J., Frystyk H., Masinter L., Leach P., and Berners-Lee T., “RFC2616-Hypertext Transfer Protocol- HTTP/1.1,” 1999.

[11] Gilchrist J. and Cuhadar A., “Parallel Lossless Data Compression using on the Burrows-Wheeler Transform,” International Journal of Web and Grid Services, vol. 4, no. 1, pp. 117-135, 2008.

[12] Gilchrist J. and Cuhadar A., “Parallel Lossless Data Compression Based on the Burrows- Wheeler Transform,” in Proceeding of Advanced Information Networking and Applications, Niagara Falls, pp. 877-884, 2007.

[13] Jagadish H., Ng R., Ooi B., and Tung A., “ItCompress: an Iterative Semantic Compression Algorithm, Data Engineering,” in Proceeding of 20th International Conference on Data Engineering, Boston, pp. 646-657, 2004.

[14] Jyrki A. and Lode V., Data compression using Zopfli, https://zopfli.googlecode.com/files/Data_compres sion_using_Zopfli.pdf , Last Visited 2014.

[15] Microsoft Corporation, http://www.microsoft.com/technet/prodtechnol/W indowsServer2003/Library/IIS/d52ff289-94d3- 4085-bc4e-24eb4f312e0e.mspx?mfr=true, Last Visited 2014.

[16] Shanmugasundaram S. and Robert L., “A Comparative Study of Text compression Algorithms,” International Journal of Wisdom Based Computing, vol. 1, no. 3, pp. 68-76, 2011.

[17] Zopfli Compression Algorithm-Google Project Hosting, https://code.google.com/p/zopfli/downloads/list, Last Visited 2014. Satpal Kushwaha is an Associate Professor, at MITRC, Alwar (Rajasthan). He has done his M.Tech. from RTU, Kota, B.E. from University of Rajasthan, Jaipur. He has 8 years of teaching and research experience. His research interests are Information Security, Network Security and Big Data. Rama Challa is Professor, at NITTTR, Chandigarh. He has done his Ph.D. from IIT Kharagpur, M.Tech. from CUSAT, Cochin and B. Tech from JNTU, Hyderabad. He has 18 years of teaching and research experience. His research interests are Wireless Networks, Distributed Computing, Cryptography, and Network Security. Hemant Saini is pursuing M. Tech in Computer Science and Engineering from Rajasthan Technical University, Kota. He is a Red hat Certified Engineer. He has completed his B. Tech in Information Technology from MLV Government Textile and Engineering College. He is having 2 years of industrial experience and one year of academic experience. His research interests are Computer Network and Security, Wireless Networks.