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Reseach Article

Performance Analysis of Mobile Memory Optimization Techniques

Published on December 2013 by Deepali D. Kayande, Jignyasa Sanghvi
National Conference on Innovative Paradigms in Engineering & Technology 2013
Foundation of Computer Science USA
NCIPET2013 - Number 1
December 2013
Authors: Deepali D. Kayande, Jignyasa Sanghvi

Deepali D. Kayande, Jignyasa Sanghvi . Performance Analysis of Mobile Memory Optimization Techniques. National Conference on Innovative Paradigms in Engineering & Technology 2013. NCIPET2013, 1 (December 2013), 16-21.

author = { Deepali D. Kayande, Jignyasa Sanghvi },
title = { Performance Analysis of Mobile Memory Optimization Techniques },
journal = { National Conference on Innovative Paradigms in Engineering & Technology 2013 },
issue_date = { December 2013 },
volume = { NCIPET2013 },
number = { 1 },
month = { December },
year = { 2013 },
issn = 0975-8887,
pages = { 16-21 },
numpages = 6,
url = { /proceedings/ncipet2013/number1/14695-1307/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 National Conference on Innovative Paradigms in Engineering & Technology 2013
%A Deepali D. Kayande
%A Jignyasa Sanghvi
%T Performance Analysis of Mobile Memory Optimization Techniques
%J National Conference on Innovative Paradigms in Engineering & Technology 2013
%@ 0975-8887
%N 1
%P 16-21
%D 2013
%I International Journal of Computer Applications

SMSLingo, a hybrid compression technique is a conjunction of RLE with static dictionary encoders based on lossless reversible transformation. This will be used for text file compression to offer better compression ratio and allow better utilization of internal memory on Android platform. The idea behind the technique is of converting the normal English text into short-form words using static dictionary and then applying Run Length Encoding (RLE) technique on this converted short-form text. Experimental results are evaluated and comparison is made between 3 text compression techniques, Huffman Coding, RLE and SMS Lingo. Promising rise is seen in the achieved results using the SMS Lingo compression algorithm in comparison with other available methods. Also this application is reasonably smaller in size as compared to the size of default SMS application present on Android platforms and with the other SMS compressor applications present for the platform. The RAM and cache memory consumption is around 3 MB for this application where the default Messaging application requires around 8 MB. Thus the proposed hybrid technique is reasonable with respect to RAM as well as cache memory consumption.

  1. Deepali Kayande, Urmila Shrawankar, "SMS Lingo: A hybrid text compression technique for mobile storage utilization", International Conference on Advances in Modeling, Optimization and Computing 2011
  2. Ningde Xie, et al. , "Using Lossless Data Compression in Data Storage Systems", IEEE Transactions on Computers, Vol. 60, No. 3, March 2011.
  3. Mo yuanbin, et al. , "A data compression algorithm based on adaptive Huffman code for Wireless Sensor Networks", Fourth International Conference on Intelligent Computation Technology and Automation 2011.
  4. Ahmad Affandi, et al. , "The Application of Text Compression to Short Message Service Using Huffman Table", Jurnal Generic Indonesia 2011.
  5. Stefan Böttcher, et al. , 2011 , Search and Modification in Compressed Texts, Data Compression Conference,
  6. S. R. Kodituwakku and U. S. Amarasinghe, 2010, Comparison of Lossless Data Compression Algorithms for Text Data, Indian Journal of Computer Science and Engineering, Vol 1 No 4.
  7. Rui Yang, Hong Cai, 2009, Research and Design of Short Message Service System Based on ARM and GPRS, Second International Symposium on Computational Intelligence and Design.
  8. Liu Pu, 2009, Performance Analysis of Short Message Service, International Symposium on Intelligent Ubiquitous Computing and Education.
  9. L. Robert and R. Nadarajan, 2009, Simple lossless preprocessing algorithms for text compression, IET Softw. , Vol. 3, Iss. 1, pp. 37–45.
  10. Xibo Wang, Yanting Yang, 2009, Method and Implementation of Sending and Receiving Mobile Phone Messages, International Forum on Computer Science-Technology and Applications.
  11. Mauro Teófilo, et al. , 2009, Ulmo: A system to Enable Mobile Applications Personalization by Binary SMS, Fourth International Multi- Conference on Computing in the Global Information Technology.
  12. Stephan Rein et al. , 2006, Low-Complexity Compression of Short Messages, Data Compression Conference (DCC).
  13. Jan L´ansk´y, Michal ?Zemli?cka, 2009, Compression of Small Text Files using Syllables, Data Compression Conference (DCC).
  14. Ming-Bo Lin, et al. , 2006, A Lossless Data Compression and Decompression Algorithm and Its Hardware Architecture, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 14, No. 9, September.
  15. B. S. Shajeemohan, Dr. V. K. Govindan, 2005, Compression Scheme for Faster and Secure Data Transmission over Networks, International Conference on Mobile Business (ICMB).
  16. Timm Euler, 2006, Tailoring Text Using Topic Words: Selection and Compression, 13th International Workshop on Database and Expert Systems Applications (DEXA).
  17. Michelle Effros, et al. , 2002, Universal Lossless Source Coding With the Burrows Wheeler Transform, IEEE Transactions on Information Theory, Vol. 48, No. 5.
  18. S. Kwong and Y. F. Ho, 2001, A Statistical Lempel-Ziv Compression Algorithm for Personal Digital Assistant (PDA), IEEE Transactions on Consumer Electronics, Vol. 47, No. 1.
  19. David Salomon, Data Compression- The Complete Reference, Third Edition.
  20. The Oxford English Dictionary, http://www. indiana. edu/~letrs/help- services/QuickGuides/oed-abbr. html
  21. Standard Word Abbreviations, http://www. acs. utah. edu/acs/qa_standards/psstd02a. htm
  22. Business English, http://www. learn-english-today. com/business-english/abbreviations. html
Index Terms

Computer Science
Information Sciences


Sms Compression Internal Memory Android Platform Memory Optimization Run Length Encoding Dictionary Encoders.