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Compression using Matrix Folding Algorithm

Authors :
Harshita Chadha
Neelam Sharma
Nitish Pathak
Gaurav Jindal
Source :
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO).
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

Space optimization is a particular phenomenon which has puzzled the computer programmers worldwide. More and more data needs to be stored into ever decreasing space. Several techniques are utilized to either decompress the files or better manage the memory. The first aspect involves the mathematics behind the conversion and the second aspect involves physics to store more data on to smaller chips. The proposed formulation i.e. The Matrix Folding Algorithm serves the first aspect of Space optimization by making use of mathematical calculations to reduce the size of a matrix. Matrix Folding Algorithm is a technique to reduce the space occupied by a square matrix to a level of 25% of the original size. The algorithm is based on mathematical calculations applied on the original values in order to double fold the matrix first from right to left and then from bottom to top. Like many other algorithms this one also has limitations that the original matrix should have numbers ranging from 0 through 15 only when we consider a system where the integer takes 2 bytes of space. And the matrix should have numbers ranging from 0 through 255 only when we consider a system where the integer takes 4 bytes of space.

Details

Database :
OpenAIRE
Journal :
2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)
Accession number :
edsair.doi...........80a998177fade752edaa50e2433c3f49