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1. Introduction
A graph labeling is an assignment of integers from 1 to
We consider the finite undirected graph
A labeling
In this paper, we consider for a total
[figures omitted; refer to PDF]
Baca et al. [2] in 2007 started to investigate the total vertex irregularity strength of a graph, an invariant analogous to the irregularity strength for total labelings. There are not many graphs for which the exact values of their total vertex irregularity strength are known. Baca et al. [2] have determined the total vertex irregularity strengths for some classes of graphs, namely, cycles, stars, and prisms. Nurdin et al. have determined the total vertex irregularity strengths of a disjoint union of
In this paper, we determine exact value of the total vertex irregularity strength of the hexagonal cluster graph with
2. Hexagonal Cluster Graph
In this section, we give the definition of hexagonal cluster graphs. The hexagonal cluster graph with
[figure omitted; refer to PDF]
Some interconnection networks are designed, and some are borrowed from nature. For example, hypercubes, complete binary trees, butterflies, and torus networks are some of the designed architectures. Grids, hexagonal networks, honeycomb networks, and diamond networks, for instance, bear resemblance to atomic or molecular lattice structures. They are called natural architectures. The advancement of large scale integrated circuit technology has enabled the construction of complex interconnection networks. Besides that, the hexagonal cluster graphs have been studied as models of organic compounds build up entirely from benzene rings, social networks, and wireless sensor networks. Graph theory provides a fundamental tool for designing and analyzing such networks [7–11].
In [2], Baca et al. studied the lower bound of
Theorem 1.
If
3. Results and Discussion
In this paper, we have proved that the total vertex irregularity strength of the hexagonal cluster graph (network) with
Theorem 2.
For
Proof.
Since the number of vertices of
To find that
Note that there are
In
Now, consider all vertices and all edges in the outer cycle
To label some of vertices and all edges in
To label all of edges in
All of edges of
Order the temporary weight of all vertices and rename them by
Based on equation (6), we have that
Besides that, from Algorithms 1 and 2, we can see that
Based on Statements (7) and (8), we conclude that the function construction with Algorithms 1 and 2 is a total vertex irregular
Based on equations (3) and (9), we find equation (2), i.e.,
As illustration, we shall use Algorithms 1 and 2 to construct a total vertex irregular 25-labeling on
Now, we use Algorithm 3 to label some of vertices and all edges in
For
Then, use Algorithm 4 to label all edges in
Algorithm 1: Algorithm for labeling all edges of the outer cycle of L1.
Step 1. For
Step 2. For
Step 3. Label all edges between
Step 4. Label the remaining edges of
Algorithm 2: Algorithm for labeling all other edges in HC(n).
K2t−1=(S2t−1+2−K2t−2)/3, Step A. Label all of edges of the outer cycle in
Step B. Label all of the remaining edges from
Step C. Label all of the remaining edges in
Algorithm 3: Algorithm for labeling all edges of the outer cycle of L1 of HC(4).
Step 1. For
Step 2. For
Step 3. Label all edges between
Step 4. Label the remaining edges of
Algorithm 4: Algorithm for labeling all other edges in HC(4).
Step A. Label all edges of the outer cycle in
Step B. Label all of the remaining edges from
Step C. Label all of the remaining edges in
4. Conclusions
In this paper, we obtained the precise values for the total vertex irregularity strength of the hexagonal cluster graphs
Acknowledgments
This research was supported by the Basic Science Research Program, National Research Foundation of Korea, Ministry of Education, (NRF-2018R1D1A1B07049584) and Basic Research Superior College, Directorate of Research and Community Service, Ministry of Research, Technology and Higher Education, Republic of Indonesia (007/SP2H/AMD/LT/DRPM/2020).
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Abstract
For a simple graph
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1 Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Hasanuddin, Makassar 40133, Indonesia
2 Department of Mathematics Education, Daegu Catholic University, Gyeongsan 38430, Republic of Korea
3 Department of Statistic, Faculty of Mathematics and Natural Sciences, University of Hasanuddin, Makassar 40133, Indonesia
4 Department of Mathematics, Maros Muhammadiyah University, Maros, Indonesia