Efficient VLSI architecture for the parallel dictionary LZW data compression algorithm

Safieh, Malek; Freudenberger, Jürgen

doi:10.1049/iet-cds.2018.5017

Cited by 11 publications

(3 citation statements)

References 19 publications

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“…The power data are compressed in the MATLAB simulation environment, and the optimal dictionary parameters of DPDLZW algorithm are selected. The performance is then compared to four other lossless compression algorithms: the LZW algorithm, the LZW algorithm with the FIFO strategy, Huffman algorithm, and PDLZW algorithm [34].…”

Section: Simulation Experimentsmentioning

confidence: 99%

A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

Wu,

Xu,

et al. 2023

IEEE Access

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With the rapid development of smart grid (SG) technologies, massive system data has been generated for SG for grid operation status monitoring and fault warning, this massive integrated data has brought great challenges for data transmission and storage. Thus, the breakthrough of data compression technology has become more and more important for data processing, this proposal, a lossless data compression method is proposed. The proposed method improves the Lempel-Ziv-Welch (LZW) algorithm. Specifically, the proposed method employs a parallel search approach to search the index of the dictionary globally by dividing the dictionary into several small dictionaries of different sizes and bit widths. In addition, the dynamic variable-length coding method is used as the output code which can offer flexible bit widths instead of fixed values, and the optimal dictionary partition combination and size parameters are selected to construct dictionaries. At last, the improved algorithm is cascaded with Huffman algorithm to form the proposed data compression algorithm. The data compression efficiency has been successfully verified by comparing with conventional Huffman and LZW data compression algorithms through data simulation, and it is observed to offer a better compression ratio than those methods with only LZW algorithm or Huffman algorithm, and save storage space effectively. More than this, the proposed method has realized lossless compression for power system data and guaranteed the integrity of the data, which will have better applicability for dealing with any similar information data.INDEX TERMS Lossless data compression, smart grid, Huffman algorithm, LZW algorithm.

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Section: Simulation Experimentsmentioning

confidence: 99%

A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

Wu,

Xu,

et al. 2023

IEEE Access

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“…Thus, it is required to implement the optimal techniques for partitioning of address space. The work addressed in [24] mitigated the memory size of parallel dictionaries by implementing a recursive dictionary structure and a word partitioning technique. However, it suffers from small loss of compression gain due to the increased RAM size of dictionaries.…”

Section: Introductionmentioning

confidence: 99%

Quantum-dot Cellular Automata Based Lossless CFA Image Compression Using Improved and Extended Golomb-rice Entropy Coder

2022

IJIES

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This article presents an efficient hardware architecture of lossless image compression mechanism using colour filter array (CFA) for wireless camera networks. Recently, Quantum-dot cellular automata (QCA) technology has been widely using in the field of VLSI, thus the proposed compressor is developed using QCA technology to mitigate the area, and power as compared to standard CMOS technology. In addition, an improved and extended Golomb-Rice entropy coder (IEGREC) is proposed to reduce the memory requirement, and computational complexity. The IEGREC approach eliminates the requirement of context module, which is a major component in lossless image compressor architectures and its memory to lessen the hardware resource utilization. Further, to maintain the pixel connectivity and higher compression ratio (CR), the proposed architecture utilizes the adaptive Golomb-Rice (GR) parameter prediction and control module. Finally, packer module is used to maintain the flow of output compressed bit stream. The extensive simulation results show that proposed QCA-IEGREC method performs superior as compared to state-of-art approaches in terms of lesser area as 3700 gate count, and reduced power of 1.02 mW, and even image quality statistics such as 18.78dB of peak signal-to-noise ratio (PSNR), 152.3 of figure-ofmerit (FOM), and 29.3 of CR.

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“…Recently, due to the extremely rapid increase in the amount of information transmitted, computer networksare overloaded due to the low bandwidth of existing communication channels. This problem can be solved in two ways: by replacing existing communication lines with new ones with greater bandwidth, or by introducing new methods of data compression [1][2][3][4][5][6][7]. The first method requires significant financial costs, in addition, it is not always possible to replace communication lines; more often it is more advisable to use existing lines for data transmission than to lay new ones.…”

Section: Introductionmentioning

confidence: 99%

Increasing the efficiency of information transmission in communication channels

Zhurakovskyi

Boiko

Druzhynin

et al. 2020

IJEECS

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<span lang="EN-US">This paper discusses compression methods focused on data transmission over communication channels. The characteristics of different algorithms for different types of incoming data are analyzed. The purpose of this study is to evaluate the speed of operation of each of the compression algorithms for different types of information and different compression parameters, on the basis of the obtained results to make recommendations for the application of compression methods in systems critical to the performance of the algorithm. Based on the results of the analysis, the methods of compression that can be used in communication channels are selected: LZW, LZH, Vitter and matrix. The practical research of the selected methods on different information flows (text, graphics, measurement data, combined data) was carried out, their comparative analysis was performed. Research has highlighted compression methods that give the most optimal results in each case. Comparative evaluation of algorithms for different parameters is made, the possibility of data compression implementation in systems running in real time is analyzed. Based on the results of the study, recommendations are made for the application of particular compression methods in specific conditions.</span>

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Efficient VLSI architecture for the parallel dictionary LZW data compression algorithm

Cited by 11 publications

References 19 publications

A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

A Dynamic and Parallel Two-Stage Lossless Data Compression Method for Smart Grid

Quantum-dot Cellular Automata Based Lossless CFA Image Compression Using Improved and Extended Golomb-rice Entropy Coder

Increasing the efficiency of information transmission in communication channels

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