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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
