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DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems

A. Arokiaraj Jovith1, S. Rama Sree2, Gudikandhula Narasimha Rao3, K. Vijaya Kumar4, Woong Cho5, Gyanendra Prasad Joshi6, Sung Won Kim7,*

1 Department of Networking and Communications, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, 603203, India
2 Department of Computer Science Engineering, Aditya Engineering College, Surampalem, Andhra Pradesh, 533437, India
3 Department of Computer Science and Engineering, Vignan's Institute of Information Technology, Visakhapatnam, 530049, India
4 Department of Computer Science and Engineering, Vignan's Institute of Engineering for Women, Visakhapatnam, 530049, India
5 Department of Software Convergence, Daegu Catholic University, Gyeongsan, 38430, Korea
6 Department of Computer Science and Engineering, Sejong University, Seoul, 05006, Korea
7 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan-si, Gyeongbuk-do, 38541, Korea

* Corresponding Author: Sung Won Kim. Email: email

Computers, Materials & Continua 2023, 74(3), 6429-6444. https://doi.org/10.32604/cmc.2023.031817

Abstract

The exponential growth of data necessitates an effective data storage scheme, which helps to effectively manage the large quantity of data. To accomplish this, Deoxyribonucleic Acid (DNA) digital data storage process can be employed, which encodes and decodes binary data to and from synthesized strands of DNA. Vector quantization (VQ) is a commonly employed scheme for image compression and the optimal codebook generation is an effective process to reach maximum compression efficiency. This article introduces a new DNA Computing with Water Strider Algorithm based Vector Quantization (DNAC-WSAVQ) technique for Data Storage Systems. The proposed DNAC-WSAVQ technique enables encoding data using DNA computing and then compresses it for effective data storage. Besides, the DNAC-WSAVQ model initially performs DNA encoding on the input images to generate a binary encoded form. In addition, a Water Strider algorithm with Linde-Buzo-Gray (WSA-LBG) model is applied for the compression process and thereby storage area can be considerably minimized. In order to generate optimal codebook for LBG, the WSA is applied to it. The performance validation of the DNAC-WSAVQ model is carried out and the results are inspected under several measures. The comparative study highlighted the improved outcomes of the DNAC-WSAVQ model over the existing methods.

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APA Style
Jovith, A.A., Sree, S.R., Rao, G.N., Kumar, K.V., Cho, W. et al. (2023). DNA computing with water strider based vector quantization for data storage systems. Computers, Materials & Continua, 74(3), 6429-6444. https://doi.org/10.32604/cmc.2023.031817
Vancouver Style
Jovith AA, Sree SR, Rao GN, Kumar KV, Cho W, Joshi GP, et al. DNA computing with water strider based vector quantization for data storage systems. Comput Mater Contin. 2023;74(3):6429-6444 https://doi.org/10.32604/cmc.2023.031817
IEEE Style
A.A. Jovith et al., "DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems," Comput. Mater. Contin., vol. 74, no. 3, pp. 6429-6444. 2023. https://doi.org/10.32604/cmc.2023.031817



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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