Research Article
A New Algorithm for Lossless Data Compression Based of Time Clock Mechanism
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 186 - Issue 43 |
| Published: September 2024 |
| Authors: Chandni Keshri, Bhanu Prakash Lohani |
10.5120/ijca2024924042
|
Chandni Keshri, Bhanu Prakash Lohani . A New Algorithm for Lossless Data Compression Based of Time Clock Mechanism. International Journal of Computer Applications. 186, 43 (September 2024), 10-14. DOI=10.5120/ijca2024924042
@article{ 10.5120/ijca2024924042,
author = { Chandni Keshri,Bhanu Prakash Lohani },
title = { A New Algorithm for Lossless Data Compression Based of Time Clock Mechanism },
journal = { International Journal of Computer Applications },
year = { 2024 },
volume = { 186 },
number = { 43 },
pages = { 10-14 },
doi = { 10.5120/ijca2024924042 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2024
%A Chandni Keshri
%A Bhanu Prakash Lohani
%T A New Algorithm for Lossless Data Compression Based of Time Clock Mechanism%T
%J International Journal of Computer Applications
%V 186
%N 43
%P 10-14
%R 10.5120/ijca2024924042
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Data compression is pivotal for optimizing storage and enhancing transmission efficiency in modern computing systems. This paper introduces a novel lossless data compression algorithm based on a time clock mechanism. The proposed algorithm, termed Time Clock Compression (TCC), leverages a temporal encoding strategy to minimize redundancy by effectively capturing data patterns with high temporal precision. The results indicate that TCC is particularly advantageous for real-time applications and large-scale data environments where rapid processing and efficient storage are critical. This innovation presents a promising data compression, offering a robust solution for various industries reliant on efficient data management.
References
- Sayood, K. (2012). Introduction to Data Compression. Elsevier.
- Salomon, D., & Motta, G. (2010). Handbook of Data Compression. Springer.
- Pennebaker, W. B., & Mitchell, J. L. (1993). JPEG Still Image Data Compression Standard. Springer.
- Ziv, J., & Lempel, A. (1977). A Universal Algorithm for Sequential Data Compression. IEEE Transactions on Information Theory, 23(3), 337-343.
- Huffman, D. A. (1952). A Method for the Construction of Minimum-Redundancy Codes. Proceedings of the IRE, 40(9), 1098-1101.
- M. A. Bassiouni, "Data Compression in Scientific and Statistical Databases", IEEE Transactions on Software Engineering, vol. SE-11, no. 10, pp. 1047-1058, 1985.
- R. Bayer and E. McCreight, "Organization and maintenance of large ordered indexes", Acta Informat, vol. 1, pp. 173-189, 1972.
- J. Goldstein, R. Ramakrishnan and U. Shaft, Compressing Relations and Indexes, December 1997.
- V. Kesri, " A New Algorithm to Provide all Solutions of SSP Problem" International Journal of Computer Applications, vol. 178, number 5, p. 20–25, 2017.
- Christopher H. Messom, Gourab Sen Gupta and Serge N. Demidenko “Hough Transform Run Length Encoding for Real Time Image Processing” IEEE transactions on instrumentation and measurement, vol. 56, no. 3, June 2007.
- Nikolay Manchev “Parallel algorithm for Run Length Encoding”, Proceedings of third international conference on information theory, 2006.
- J. Trein, A.Th.Schwarzbacher, B. Hoppe and K.-H. Noffz “A Hardware Implementation of a Run Length Encoding Compression Algorithm with Parallel Inputs”, ISSC 2008, Galway, June 18-19.
Index Terms
Keywords