Characterizing Interconnection Networks in Terms of Complexity via Entropy Measures

One of the most recent advancements in graph theory is the use of a multidisciplinary approach to the investigation of specific structural dependent features, such as physico-chemical properties, biological activity and the entropy measure of a graph representing objects like a network or a chemical...

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Bibliographic Details
Main Authors: Jinhong Zhang, Asfand Fahad, Muzammil Mukhtar, Ali Raza
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Symmetry
Subjects:
Online Access:https://www.mdpi.com/2073-8994/15/10/1868
Description
Summary:One of the most recent advancements in graph theory is the use of a multidisciplinary approach to the investigation of specific structural dependent features, such as physico-chemical properties, biological activity and the entropy measure of a graph representing objects like a network or a chemical compound. The ability of entropy measures to determine both the certainty and uncertainty about objects makes them one of the most investigated topics in science along with its multidisciplinary nature. As a result, many formulae, based on vertices, edges and symmetry, for determining the entropy of graphs have been developed and investigated in the field of graph theory. These measures assist in understanding the characteristics of graphs, such as the complexity of the networks or graphs, which may be determined using entropy measures. In this paper, we derive formulae of entropy measures of an extensively studied family of the interconnection networks and classify them in terms of complexity. This is accomplished by utilizing all three tools, including analytical formulae, graphical methods and numerical tables.
ISSN:2073-8994