Computer Architectures Empowered by Sierpinski Interconnection Networks utilizing an Optimization Assistant

Authors

  • Muhammad Waseem Iqbal Department of Software Engineering, Superior University, Pakistan | Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Malaysia
  • Nizal Alshammry Department of Computer Sciences, Faculty of Computing and Information Technology, Northern Border University, Saudi Arabia
Volume: 14 | Issue: 4 | Pages: 14811-14818 | August 2024 | https://doi.org/10.48084/etasr.7572

Received: 20 April 2024 | Revised: 5 May 2024 | Accepted: 7 May 2024 | Online: 2 August 2024


Corresponding author: Nizal Alshammry

Abstract

The current article discusses Sierpinski networks, which are fractal networks with certain applications in computer science, physics, and chemistry. These networks are typically used in complicated frameworks, fractals, and recursive assemblages. The results derived in this study are in mathematical and graphical format for particular classes of these networks of two distinct sorts with two invariants, K-Banhatti Sombor (KBSO) and Dharwad, along with their reduced forms. These results can facilitate the formation, scalability, and introduction of novel interconnection network topologies, chemical compounds, and VLSI processor circuits. The mathematical expressions employed in this research offer modeling insights and design guidelines to computer engineers. The derived simulation results demonstrate the optimal ranges for a certain network. The optimization assistant tool deployed in this work provides a single maximized value representing the maximum optimized network. These ranges can be put into service to dynamically establish a network according to the requirements of this paper.

Keywords:

Sierpinski, invariants, interconnection network, network graph, Dharwad, k-Banhatti sombor indices, maple, inclusive innovation

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How to Cite

[1]
M. W. Iqbal and N. Alshammry, “Computer Architectures Empowered by Sierpinski Interconnection Networks utilizing an Optimization Assistant”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 4, pp. 14811–14818, Aug. 2024.

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