https://doi.org/10.1140/epjp/s13360-023-04725-4
Regular Article
Interconnection network analysis through ve-degree-based information functional entropy and complexity
1
Pingdingshan University, Pingdingshan, China
2
National University of Philippines, Manila, Philippines
3
School of Mathematical Sciences, Zhejiang Normal University, 321004, Jinhua, China
4
Centre for Advanced Studies in Pure and Applied Mathematics, Bahauddin Zakariya University, Multan, Pakistan
Received:
15
September
2023
Accepted:
20
November
2023
Published online:
14
December
2023
In modern era of science, the network analysis theory is employed to diverse directions including thermal transport, prediction of cetane numbers, artificial intelligence for sustainable supply chain, establishing public policy via social networks, postoperative health monitoring and phase change in a storage tank. By analyzing the complexity of the networks, we are able to acquire information about the performance/behavior of these systems and enhance their efficiency. One way to determine the complexity is by means of the entropy measurements of these networks. The ability of entropy measures to determine both the certainty and uncertainty about an object makes them one of the most investigated topics in science. Depending on which part of the structure is more dominant, the system’s behavior may depend on the node (vertex) or connection (edge) structure or complexity. In this study, we construct ve-degree-based information functionals to introduce formulae for entropy measures and apply them on certain interconnection networks (ICNs). The entropies are defined in such a way that they are associated with the ve-degree-dependent topological indices (TIs). To show how our examined model demonstrates the comparison between edge-based complexity of ICNs of different types, we obtain numerical data tables and graphical patterns from our proved results. The proposed entropy formulae helped to determine entropy patterns between Benes network and its derived class, describe complexity comparisons, and thus test positively on a recently introduced scale of usefulness.
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© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
