Pram-Based Algorithm for Perfect Difference Network Analysis
Bibliographic Data
| ID | 22198636 |
|---|---|
| Authors | Pinki Sharma (0000-0002-0356-4536, Amicable Knowledge Solution University), Shravan Kumar Tripathi (Awadhesh Pratap Singh University), Rakesh Kumar Katare (0009-0002-4981-4972, Awadhesh Pratap Singh University), Akhilesh A Waoo (0000-0001-6788-710X, Amicable Knowledge Solution University) |
| Year | 2024 |
| Volume | 5 |
| Issue | 1 |
| Publication date | 2024-01-31 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ShodhKosh: Journal of Visual and Performing Arts (JOURNAL) |
| Journal identifiers | ISSN: 2582-7472 • E-ISSN: 2582-7472 |
| Publisher | Granthaalayah Publications and Printers (PUBLISHER • IN) |
| DOI | 10.29121/shodhkosh.v5.i1.2024.1877 |
| OpenAlex | W4402491202 |
| Language | EN |
| References cited | 3 |
Perfect Difference Networks (PDNs) are fundamental in various computational tasks, particularly in areas like signal processing, image processing, and cryptography. Analyzing PDNs efficiently is essential for optimizing their performance. In this paper, we present a Parallel Random-Access Machine (PRAM) algorithm specifically designed for PDN analysis. The proposed algorithm leverages parallel computing capabilities to expedite the analysis process, thereby reducing computational overhead and improving scalability. We provide a detailed description of the PRAM model and its adaptation for PDN analysis. Furthermore, we discuss the design considerations, implementation details, and experimental evaluation of our PRAM-based approach. Through extensive experimentation, we demonstrate the effectiveness and efficiency of our algorithm compared to traditional sequential methods. Our research contributes to advancing the state-of-the-art in PDN analysis techniques, offering scalable solutions suitable for large-scale PDNs
Algorithm · Computer Science · Data Management and Algorithms · Energy Efficient Wireless Sensor Networks · Mobile Ad Hoc Networks
| Highly cited | No |
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