Exploring the Tiny Encryption Algorithm: A Comparative Analysis of Parallel and Sequential Computation
Tiny Encryption Algorithm, Parallel Machines, Encryption, Computation, Fast Software Encryption
The Tiny Encryption Algorithm (TEA) is renowned for its strong security and impressive speed, making it highly suitable for lightweight encryption needs in diverse applications. This research paper delves into the investigation of TEA's efficiency by examining the influence of various execution parameters. The study specifically focuses on exploring the impact of factors such as data size, processing type, and the number of processing units in the execution machine on TEA's performance. Through this analysis, valuable insights can be gained to optimize TEA's usage and enhance its overall effectiveness. In addition, this paper introduces a robust model designed to efficiently execute the TEA on parallel machines with large-scale data. The proposed model utilizes a master processor for data splitting and gathering, along with multiple slave processors for executing distributed data. To assess the performance of the TEA algorithm, several experiments were conducted, evaluating factors such as efficiency, execution time, and speedup. These experiments involved varying numbers of plaintexts and key sizes, conducted on both serial and parallel machines, including different cores systems. The TEA algorithm was implemented in C/C++ language using the Message Passing Interface (MPI) library and tested on the high-performance IMAN1 super-computer. The study reveals the significant value of parallel systems in enhancing the overall efficiency of TEA (Tiny Encryption Algorithm), thereby playing a crucial role in the development of secure embedded systems within a short timeframe. The findings demonstrate that parallel processing significantly boosts the computational power of encryption algorithms by distributing computational tasks across multiple processors or cores. Remarkably, the study achieves a substantial decrease in execution time, with a record of 13.258 seconds for a 512k plaintext and 512 key size on a 128-CPU machine. Additionally, the study showcases impressive speed-up across various approaches, highlighting the impactful achievements that fuel further research in this field.
"Exploring the Tiny Encryption Algorithm: A Comparative Analysis of Parallel and Sequential Computation", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 7, page no.693 - 702, July-2023, Available :https://ijsdr.org/papers/IJSDR2307101.pdf
Volume 8
Issue 7,
July-2023
Pages : 693 - 702
Paper Reg. ID: IJSDR_207779
Published Paper Id: IJSDR2307101
Downloads: 000347270
Research Area: Computer Science & Technology
Country: Jordan-Amman-Madab-armman Strees Buildin - 5, floo, Amman, Jordan
DOI: http://doi.one/10.1729/Journal.35208
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
