Computer Systems Science & Engineering
DOI:10.32604/csse.2021.014896
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Article

Comparative Study of Valency-Based Topological Descriptor for Hexagon Star Network

Ali N. A. Koam1, Ali Ahmad2,*and M. F. Nadeem3

1Department of Mathematics, College of Science, Jazan University, New Campus, Jazan, 2097, Saudi Arabia
2College of Computer Science & Information Technology Jazan University, Jazan, Saudi Arabia
3Department of Mathematics, COMSATS University Islamabad, Lahore Campus, Lahore, 54000, Pakistan
*Corresponding Author: Ali Ahmad. Email: ahmadsms@gmail.com
Received: 25 October 2020; Accepted: 13 November 2020

Abstract: A class of graph invariants referred to today as topological indices are inefficient progressively acknowledged by scientific experts and others to be integral assets in the depiction of structural phenomena. The structure of an interconnection network can be represented by a graph. In the network, vertices represent the processor nodes and edges represent the links between the processor nodes. Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks. A topological descriptor is a numerical total related to a structure that portray the topology of structure and is invariant under structure automorphism. There are various uses of graph theory in the field of basic science. The main notable utilization of a topological descriptor in science was by Wiener in the investigation of paraffin breaking points. In this paper we study the topological descriptor of a newly design hexagon star network. More preciously, we have computed variation of the Randiimages images, fourth Zagreb images, fifth Zagreb images, geometric-arithmetic images atom-bond connectivity images harmonic images symmetric division degree images first redefined Zagreb, second redefined Zagreb, third redefined Zagreb, augmented Zagreb images, Albertson images Irregularity measures, Reformulated Zagreb, and forgotten topological descriptors for hexagon star network. In the analysis of the quantitative structure property relationships (QSPRs) and the quantitative structure activity relationships (QSARs), graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds. We also gave the numerical and graphical representations comparisons of our different results.

Keywords: Topological indices; degree-based index; hexagon star network

1  Introduction

Cheminformatics is another field of modern sciences that connects chemistry, math, and other fields of science. Quantitative structure-activity relationship (QSAR) and Quantitative structure-activity relationship (QSPR) are the principle parts of cheminformatics which are useful to contemplate the physico-chemical properties of networks. A topological descriptor (TD) is a numerical total related to a structure that portray the topology of the structure and is invariant under structure automorphism. There are various uses of graph theory in the field of basic science. The main notable utilization of a TD in science was by Wiener in the investigation of paraffin breaking points [1]. From that point forward, to clarify physico-chemical properties, different TDs have been presented.

Topological descriptors (TD) are commonly partitioned into three sorts: degree, distance and spectrum based. The structures of networks can be scientifically demonstrated by a figure. The vertex represents the processor hub and an edge describes the links among processors. The topology of the figure of a network chooses the way by which any two vertices are linked by an edge. The topology of a network system can be used to obtained specific properties without a lot of stretches. The width is resolved as the most extreme separation between any two hubs in the system. The quantity of connections associated with a hub decides the level of that hub. If this number is the equivalent for all hubs in the system, the system is called regular.

TD can be effortlessly processed by utilizing the ideas of atomic topology (AT), an order dependent on the graph theory. Actually, AT has demonstrated to be a fantastic apparatus for quick and exact estimation of numerous physicochemical as well as biological properties [2,3]. So as to compute topological indices, basics of AT are utilized where chemical compound is changed over into a graph, considering the atoms and bonds are represented by vertices and edges of a graph. The basic definitions and notations are taken from the book [4]. The number of vertices adjacent to the vertex images is the degree of images, denoted as images.

TD which are obtained through the connectivity of two-dimensional structures, deliver significant connections to various properties of these structures via QSAR/QSPR resulting from the topological networks of these structures [5]. Since last few years, numerous researchers conducted for the expansion of TD because of their significance [6–9]. For detail study of TD see [10–21].

2  Degree-Based Indices

In this section, we define some degree based topological indices images

•    images, represents images as the general, second, and second modified Randiimages indices if images images and images respectively.

•    images, represents images as the general sum connectivity, sum connectivity, Zagreb and hyper Zagreb indices, if images images images and images respectively.

•    If images, then images represents generalized Zagreb index.

Similarly, if

images, images, images, images, images, images, images, images, images, images, images, images, images, images, images, we obtained fourth Zagreb images, fifth Zagreb images, geometric-arithmetic images atom-bond connectivity images harmonic images symmetric division degree images first redefined Zagreb, second redefined Zagreb, third redefined Zagreb, augmented Zagreb images, variation of the Randiimages images, Albertson images IRMimages irregularity measures, Reformulated Zagreb, and forgotten topological indices respectively.

3  Hexagon Star Network Sheet

Interconnection systems are significant in PC systems administration and used to change information between the PC and processer. In the most recent couple of years, numerous specialists structured the new interconnection systems. In an equal PC framework, interconnection organize is accustomed to expanding the exhibition. In diagram hypothesis, organize is spoken to as a chart. In this articulation, the processer spoke to by vertex and association between the units spoke to by edges. From the topology of a system, we can decide certain properties. The level of a hub is characterized as the all outnumber of connections associated with that hub. The system is supposed to be regular if each hub in the system has the same degree. In this paper, we define a new interconnection network hexagon star network. This network is a composition of triangles around a hexagon, as shown in Fig. 1.

Figure 1: The hexagon star network sheet for images, images

4  Main Results

In this section, we give results, which are used to obtained any degree-based topological descriptors. We obtained exact results of degree-based TD for hexagon star network sheet images. Vetrík [22] introduced a new method to calculate the topological indices and also in [23], we follow the same technique in this paper. Now, we presents a formula, which can be used to obtain any degree based TD.

Lemma 4.1 Let images be a hexagon star network. Then images

Proof. The graph images contains images vertices and images edges. Each vertex of images has degree 2 or 4, vertices of images can be partitioned according to their degrees. Let

This means that the set images contains the vertices of degree images. The set of vertices with respect to their degrees are as follows:

Since, images and images We partite the edges of images into sets based on degrees of its end vertices. Let

Note that images The number of edges incident to one vertex of degree 2 and other vertex of degree 4 is images, so images Now, the remaining number of edges are those edges which are incident to two vertices of degree 4, i.e., images

Hence,

After simplification, we get

Now we obtained the well-known degree based TD of hexagon star network in the following theorem.

Theorem 4.2 For the hexagon star network images, we have

the general Randic′ index of images is,

the Randiimages index of images is

the second Zagreb index of images is

the second Zagreb index of images is

Proof. For images which is the general Randiimages indices of images, we have images therefore images and images Thus by Lemma 4.1,

For images, the Randic′ index

After simplification, we get

For images the second Zagreb index is

For images, the second modified Zagreb index is

Table 1: Numerical representation of Theorem 4.2

Figure 2: Graphical comparison of Theorem 4.2

We gave graphical comparison of Theorem 4.2 in Fig. 2 and numerical values Tab. 1.

In the next theorem, we determined general sum-connectivity index, first Zagreb index and hyper-Zagreb index of the hexagon star network images.

Theorem 4.3 For the hexagon star network images, we have

the general sum-connectivity index of images is

the sum-connectivity index of images is

the first Zagreb index of images is

the hyper-Zagreb index of images is

Proof. For images which is the general sum-connectivity index of images, we have images therefore images and images Thus by Lemma 4.1,

For images sum-connectivity index of images

After simplification, we get

For images the first Zagreb index is

For images the hyper-Zagreb index is

Table 2: Numerical representation of Theorem 4.3

Figure 3: Graphical comparison of Theorem 4.3

We gave graphical comparison of Theorem 4.3 in Fig. 3 and numerical values Tab. 2.

Theorem 4.4 For the hexagon star network images, we have

the geometric-arithmetic index of images,

the atom-bond connectivity index of images,

the augmented Zagreb index of images,

Proof. For images which is the geometric-arithmetic index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the atom-bond connectivity index of images, we have images therefore images and images Thus by Lemma 4.1,

After simplification, we get

For images which is the augmented Zagreb index of images, we have images therefore images and images Thus by Lemma 4.1,

Table 3: Numerical representation of Theorem 4.4.

Figure 4: Graphical comparison of Theorem 4.4

We gave graphical comparison of Theorem 4.4 in Fig. 4 and numerical values Tab. 3.

Theorem 4.5 For the hexagon star network images, we have

the symmetric division degree index of images,

the Albertson index of images,

the harmonic index of images

Proof. For images which is the symmetric division degree index of images, we have images therefore images and images Thus by Lemma 4.1, images

For images which is the Albertson index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the harmonic index of images, we have images therefore images and images Thus by Lemma 4.1,

Table 4: Numerical representation of Theorem 4.5

Figure 5: Graphical comparison of Theorem 4.5

We gave graphical comparison of Theorem 4.5 in Fig. 5 and numerical values Tab. 4.

Theorem 4.6 For the hexagon star network images, we have

the first redefined Zagreb index of images,

the second redefined Zagreb index of images,

the third redefined Zagreb index of images

Proof. For images which is the first redefined Zagreb index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the second redefined Zagreb index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the third redefined Zagreb index of images, we have images therefore images and images Thus by Lemma 4.1,

Table 5: Numerical representation of Theorem 4.6

Figure 6: Graphical comparison of Theorem 4.6

We gave graphical comparison of Theorem 4.6 in Fig. 6 and numerical values Tab. 5.

Theorem 4.7 For the hexagon star network images, we have

the Randiimages index of images,

the Reformulated Zagreb index of images,

the forgotten index of images

the irregularity measures of images

Proof. For images which is the Randiimages index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the Reformulated Zagreb index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the forgotten index of images, we have images therefore images and images Thus by Lemma 4.1,

For images which is the irregularity measures of images, we have images therefore images and images Thus by Lemma 4.1,

4  Conclusion

The study of graphs and networks through topological descriptors is important to understand their underlying topologies. Such investigations have a wide range of applications in cheminformatics, bioinformatics and biomedicine fields, where various graph invariants based assessments are used to deal with several challenging schemes. In the analysis of the quantitative structure property relationships (QSPRs) and the quantitative structureactivity relationships (QSARs), graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds. In this paper, we study the valency-based topological descriptor for hexagon star network.

Funding Statement: The authors received no specific funding for this study.

Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.

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