CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Design and Implementation of Lempel-Ziv Data Compression using FPGA

by Gehad Mohey, Abdelhalim Zekry, Hatem Zakaria
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 12
Year of Publication: 2021
Authors: Gehad Mohey, Abdelhalim Zekry, Hatem Zakaria
10.5120/ijca2021921008

Gehad Mohey, Abdelhalim Zekry, Hatem Zakaria . Design and Implementation of Lempel-Ziv Data Compression using FPGA. International Journal of Computer Applications. 174, 12 ( Jan 2021), 38-45. DOI=10.5120/ijca2021921008

@article{ 10.5120/ijca2021921008,
author = { Gehad Mohey, Abdelhalim Zekry, Hatem Zakaria },
title = { Design and Implementation of Lempel-Ziv Data Compression using FPGA },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2021 },
volume = { 174 },
number = { 12 },
month = { Jan },
year = { 2021 },
issn = { 0975-8887 },
pages = { 38-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number12/31734-2021921008/ },
doi = { 10.5120/ijca2021921008 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:21:57.011447+05:30
%A Gehad Mohey
%A Abdelhalim Zekry
%A Hatem Zakaria
%T Design and Implementation of Lempel-Ziv Data Compression using FPGA
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 12
%P 38-45
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

When transmitting the data in digital communication, it is well desired that the transmitting data bits should be as minimal as possible, so many techniques are used to compress the data. In this paper, a Lempel-Ziv algorithm for data compression was implemented through VHDL coding. The Lempel-Ziv algorithm is one of the most widely used among lossless data compression algorithms for hardware implementation. The work in this paper is devoted to improve the compression rate, space-saving, and utilization of the Lempel-Ziv algorithm using a systolic array approach. The developed design is validated with VHDL simulations using Xilinx ISE 14.5 and synthesized on Virtex-6 FPGA chip. The results show that our design is efficient in providing high compression rates as well as improved utilization. The Throughput is increased by 50% and the design area is decreased by more than 23% with a high compression ratio compared to comparable previous designs. (

References
  1. J. Latif and Z. Ali, ‘An Efficient Data Compression Algorithm for Real-Time Monitoring Applications in Healthcare’, pp. 71–75, 2020.
  2. J. Uthayakumar and T. Vengattaraman, ‘Performance Evaluation of Lossless Compression Techniques : An Application of Satellite Images’, 2018 Second Int. Conf. Electron. Commun. Aerosp. Technol., no. Iceca, pp. 750–754, 2018.
  3. H. D. Kotha, M. Tummanapally, and V. K. Upadhyay, ‘Review on Lossless Compression Techniques’, J. Phys. Conf. Ser., vol. 1228, no. 1, 2019, doi: 10.1088/1742-6596/1228/1/012007.
  4. A. Gopinath, ‘Comparison of Lossless Data Compression Techniques’, pp. 628–633, 2020.
  5. J. Uthayakumar, T. Vengattaraman, and P. Dhavachelvan, ‘A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications’, J. King Saud Univ. - Comput. Inf. Sci., 2018, doi: 10.1016/j.jksuci.2018.05.006.
  6. A. Moffat, ‘Huffman Coding’, vol. 52, no. 4, 2019.
  7. S. T. Klein, S. Saadia, and D. Shapira, ‘Forward Looking Huffman Coding’, 2020.
  8. M. Pandey, S. Shrivastava, and S. Pandey, ‘An Enhanced Data Compression Algorithm’, pp. 1–4, 2020, doi: 10.1109/ic-ETITE47903.2020.223.
  9. C. W. Huang and J. J. Ding, ‘Efficient EEG Signal Compression Algorithm with Long Length Improved Adaptive Arithmetic Coding and Advanced Division and Encoding Techniques’, Int. Conf. Digit. Signal Process. DSP, vol. 2018-Novem, no. 1, pp. 1–5, 2019, doi: 10.1109/ICDSP.2018.8631886.
  10. J. Ziv and A. Lempel, ‘A Universal Algorithm for Sequential Data Compression’, IEEE Trans. Inf. Theory, vol. 23, no. 3, pp. 337–343, 1977, doi: 10.1109/TIT.1977.1055714.
  11. A. Gupta, A. Bansal, and V. Khanduja, ‘Modern lossless compression techniques: Review, comparison and analysis’, Proc. 2017 2nd IEEE Int. Conf. Electr. Comput. Commun. Technol. ICECCT 2017, vol. XI, no. Xii, pp. 44–51, 2017, doi: 10.1109/ICECCT.2017.8117850.
  12. U. K. H, ‘Design and Implementation of Lossless Data Compression Coprocessor using FPGA’, vol. 4, no. 05, pp. 818–822, 2015.
  13. K. Pagiamtzis and A. Sheikholeslami, ‘Content-addressable memory (CAM) circuits and architectures: A tutorial and survey’, IEEE J. Solid-State Circuits, vol. 41, no. 3, pp. 712–727, 2006, doi: 10.1109/JSSC.2005.864128.
  14. S. A. Hwang and C. W. Wu, ‘Unified VLSI systolic array design for LZ data compression’, IEEE Trans. Very Large Scale Integr. Syst., vol. 9, no. 4, pp. 489–499, 2001, doi: 10.1109/92.931226.
  15. N. Ranganathan and S. Henriques, ‘A systolic chip for LZ based data compression’, Proc. IEEE Int. Conf. VLSI Des., pp. 310–311, 1991, doi: 10.1109/ISVD.1991.185144.
  16. M. A. Abd El Ghany, A. E. Salama, and A. H. Khalil, ‘Design and implementation of FPGA- Based systolic array for LZ data compression’, Proc. - IEEE Int. Symp. Circuits Syst., pp. 3691–3695, 2007, doi: 10.5772/8872.
  17. B. Jaysree, D. Harshith, P. Deekshith, and I. B. Mahapatra, ‘Design and implementation of a reconfigurable hardware for data compression techniques : a Survey’, vol. 10, no. 03, pp. 33–40, 2020, doi: 10.9790/9622-1003023340.
  18. J. Ziv and A. Lempel, ‘Compression of Individual Sequences via Variable-Rate Coding’, IEEE Trans. Inf. Theory, vol. 24, no. 5, pp. 530–536, 1978, doi: 10.1109/TIT.1978.1055934.
  19. J. A. Storer and T. G. Szymanski, ‘Data Compression via Textual Substitution’, J. ACM, vol. 29, no. 4, pp. 928–951, 1982, doi: 10.1145/322344.322346.
  20. S. Belu and D. Coltuc, ‘RoLZ-The reduced offset LZ data compression algorithm’, ISSCS 2019 - Int. Symp. Signals, Circuits Syst., pp. 1–4, 2019, doi: 10.1109/ISSCS.2019.8801741.
  21. G. Wang, H. U. A. Peng, and Y. Tang, ‘Repair and Restoration of Corrupted LZSS Files’, IEEE Access, vol. 7, pp. 9558–9565, 2019, doi: 10.1109/ACCESS.2019.2891764.
  22. E. R. Marsh and B. R. Knapp, ‘On the design and implementation of an instrumented grinding testbed’, Sens. Rev., vol. 25, no. 1996, pp. 155–161, 2005, doi: 10.1108/02602280510585754.
Index Terms

Computer Science
Information Sciences

Keywords

Data Compression Lossless compression VHDL FPGA Design Utilization CODEC LZSS LZ77 Systolic array design

Powered by PhDFocusTM