Open Access
·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667
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The Journal of Information and Optimization Sciences (JIOS) is a world leading journal publishing high quality, rigorously peer-reviewed original research in all mathematically-oriented theoretical and applied topics in information sciences, optimization sciences and related areas since 1980. Subjects include but are not limited to:
• Information Sciences
• Optimization Sciences
• Control Theory
• Operational Research
• Decision Sciences
• Information Theory
• Information Technology
• Computer Networks and Communications
• Mathematical Programming
• Modelling and Simulation
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Issues up to 2022 co-published with and available at:
Implementing data compression techniques in database systems to enhance storage optimization
Pradnya Borkarpradnyaborkar2@gmail.comDepartment of Computer Science and Engineering Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University)Department of Computer Science and Engineering Symbiosis Institute of Technology Nagpur Campus Symbiosis International (Deemed University)Pune, Maharashtra, 440027, IndiaView full profile →
, *Sulabha Narendra PatilCorresponding authorsulbha.patil@vit.eduDepartment of Engineering Science and Humanities Vishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile →
, Gagan Tiwarigagan.tiwari@niu.edu.inDepartment of Computer Science Noida International UniversityDepartment of Computer Sciences Noida International UniversityNoida, Uttar Pradesh, 203201, IndiaView full profile →
, E. Shalinishalini@maher.ac.inDepartment of Computer Science Meenakshi College of Arts and Science Meenakshi Academy of Higher Education and ResearchChennai, Tamil Nadu, 600078, IndiaView full profile →
, Shrinivas T. Shirkandeshri.shirkande8@gmail.comDepartment of Computer Engineering S. B. Patil College of Engineering Indapur Affiliated to Savitribai Phule Pune University (SPPU) PuneDepartment of Computer Engineering S. B. Patil College of Engineering IndapurPune, Maharashtra, 413106, IndiaView full profile →
* Corresponding author · click or hover a name for details
The huge amount of digital data that is being created every second has made it hard for computer systems to store, run, and keep up with. Using perfect compression methods is a good way to get the most out of your resources while keeping the purity of your data. This research looks at how Huffman coding, LZW, and Run-Length Encoding can be used together in database storage systems. Formulations, theories, and arguments in mathematics set limits on performance and measure how efficient something is. Experiments show that this method saves a lot of space and makes queries faster, especially for bigger datasets. Findings show that systems that can compress data make them scalable, cost-effective, and long-lasting.
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