Abstract
Graph theory is a useful mathematical structure used to model pairwise relations between sensor nodes in wireless sensor networks. Graph equations are nothing but equations in which the unknown factors are graphs. Many problems and results in graph theory can be formulated in terms of graph equations. In this paper, we solved some graph equations of detour two-distance graphs, detour three-distance graphs, detour antipodal graphs involving with the line graphs.
1. Introduction
The recent rapid growth in the Internet of things has necessitated the development of new approaches to persistent issues in wireless sensor networks. These issues include minimum obstacles in the end-to-end communication path, location accuracy, latency, and delay, among others. These problems can be mitigated by using the distance graph to create local algorithms, i.e., algorithms with minimum communication rounds. We study distance graph applications in wireless sensor networks with a focus on minimum path obstacles and high localization accuracy.
A wireless sensor network (WSN) is a network of tiny wireless sensors that can sense a parameter of interest. The sensed data is forwarded to a base station through the formed ad hoc network of sensor nodes. There are many application areas of WSNs, including M2M communication and the Internet of Things (IoT). WSNs are a fundamental building block of smart homes, smart workplaces, and smart cities, among others. It has a lot of other essential purposes for modern technology, such as scientific research, rescue operations, and scientific discoveries. As sensors are a power constraint tiny devices, energy conservation for extending the network’s lifetime is a challenging issue. A wireless sensor network’s lifetime heavily depends on innovative schemes that mitigate energy consumption. The distance graph is used to form and localize an ad hoc network of sensor nodes so that sensed data can be forwarded to the base station with little energy cost.
Therefore, finding the solutions to these graph equations is essential. A lot of research has been done by many researchers during the past fifty years, and their results have made a significant contribution in graph theory.
Let X be a nontrivial finite connected graph. Every graph X with detour distance D defines a metric space. The n-distance graph of X, denoted by , is the graph with in which two vertices u and v are adjacent in if and only if . Furthermore, for each set , the detour distance graph is the graph having as its vertex set and two vertices u and v in this graph are adjacent if and only if . We denote this graph simply by . The graph is called the detour n-distance graph of X. If n equals the detour diameter of X, then this graph is called the detour antipodal graph of X, which is denoted by . A graph X is said to be a detour self n-distance graph if .
The line graph of a graph G is the graph whose vertices correspond to the edges of G and wherein two vertices are adjacent in if and best if the corresponding edges are adjacent in G.
In this work, we consider the detour distance graphs. Specifically, we solve the graph equations involving detour two-distance graphs, detour three-distance graphs, detour antipodal distance graphs, line graphs, and the complement of graphs. In addition, we solve some equations involving two-distance graphs, three-distance graphs, and antipodal distance graphs with the graphs mentioned earlier.
Harary, Heode, and Kedlacek first studied the two-distance graph. They investigated the connectedness of two-distance graphs. This graph and the relationship between the two-distance graph and line graph was further studied in [1,2,3,4,5,6,7,8,9]. In 2014, Ali Azimi and Mohammad D. X solved the graph equations and . In 2015, Ramuel P. Ching and Garces gave three characterizations of two-distance graphs and found all the graphs X such that or , which can be found in [10]. S. K Simic and some mathematicians solved some graph equations of line graphs, which can be found in [11,12,13,14,15,16,17]. In 2017, R. Rajkumar and S. Celine Prabha solved some graph equations of two-distance, three-distance and n-distance graph equations, which can be found in [18,19,20]. In 2018, R. Rajkumar and S. Celine Prabha found the characterization of the distance graph of a path which was described in [21].
Motivated by the results listed above, we solved some graph equations of distance graphs and line graphs. Other graph-theoretic terms and notations that are not explicitly defined here can be found in [2].
2. Solutions of Graph Equations of Detour Two-Distance Graphs and Line Graphs
First, we consider some graph equations of type , where and are given graphs and investigate the solution G of these equations.
The main result of solving graph equations involving detour two-distance graphs we prove in this section is the following:
Theorem 1.
Let G be a graph. Then,
- if and only if ;
- if and only if ;
- ;
- if and only if ;
- if and only if ;
- If G is connected, then
- (a)
- if and only if ;
- (b)
- if and only if ;
- (c)
- ;
- (d)
- if and only if ;
- (e)
- if and only if ;
- (f)
- ;
- (g)
- ;
- (h)
- if and only if ;
- (i)
- if and only if .
Lemma 1.
Let be an integer. Then,
Proof.
Clearly and . If , then the detour distance between any two vertices of is at least three, so . □
Proposition 1.
Let be an integer. Then,
- , , ,, ,, and if and only if ;
- , if and only if ;
- , , ,and for all .
Proof.
Clearly . Note that and . Furthermore, if , then is connected and is -regular. Therefore, the proof follows from Lemma 1. □
Proposition 2.
Let G be a graph.
- If G is connected non-unicyclic, then , , , , , , ,, , , , , , and .
- If G is disconnected, then and .
Proof.
- Let G be connected non-unicyclic. Suppose that . Then, we have , so G is unicyclic, since G is connected, which is a contradiction to our assumption that G is non-unicyclic. Thus, . The proof of the rest of the cases are similar to the above.
- Let G be disconnected. Then, , are disconnected; and are connected. Combining these pieces of information, we get the result.
□
Proposition 3.
Let G be a connected unicyclic graph but not a cycle. Then,
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- .
Proof.
- Let be the induced cycle of G. Let this cycle be . Let v be a vertex in G which is not in the cycle of G. Without loss of generality, we may assume that v is adjacent to . Then, is in , so is disconnected. However, is connected. Therefore, .
- If or , then has two components. However, has three components. Thus, .If G is the graph other than these graphs, then by the argument of part (a), is disconnected. Hence, is connected. Therefore, .
- By the structure of G, the graph is connected non-unicyclic. Let the maximum length among all the cycles in be k. Clearly . If , then any vertex in such a cycle is isolated in . If , then G is the graph obtained from by adding a pendent edge to any of its vertex. In this case, is disconnected. Thus, .
- By part (c), is disconnected. However, is connected except for the graph . Therefore, . If , then has two isolated vertices. However, has exactly one isolated vertex. Thus, .
- If or , then is disconnected and so is disconnected. Thus, .If G is the graph other than these graphs, then the maximum length among all the cycles in is at least six. Then, any vertex in such a cycle is isolated in . Therefore, .
- By part (e), is disconnected. Thus, by a similar argument as in part (d), we get .
- By part (c), is disconnected. Therefore, is disconnected and so .
- If G is the graph other than the graph , then is connected. By part (c), is disconnected. Thus, is disconnected and so . If , then contains at least two isolated vertices. However, has exactly one isolated vertex. Thus, .
- By part (c), is disconnected. Therefore, is disconnected and so .
- The proof is similar to the proof of part (h), since is also disconnected.
- By part (e), is disconnected. Thus, is also disconnected. Consequently, we get .
- By part (e), is disconnected. However, is connected except for the graph . So . If , then has at least two isolated vertices but has exactly one isolated vertex.Therefore, .
- By part (a) is disconnected. Thus, is connected and .
- If or , then has two components. However, has three components. Therefore, .If G is the graph other than these graphs, then by the argument of part (a), is disconnected and so is disconnected. Hence, is connected. Therefore, .
□
Combining Propositions 1–3, we get the proof of Theorem 1.
3. Solutions of Graph Equations of Detour Three-Distance Graphs and Line Graphs
The main result on solving graph equations involving three-distance graphs we prove in this section is the following:
Theorem 2.
Let G be a graph. Then,
- if and only if ;
- if and only if ;
- if and only if or ;
- If G is connected, then
- (a)
- if and only if or ;
- (b)
- if and only if ;
- (c)
- if and only if ;
- (d)
- if and only if or ;
- (e)
- if and only if ;
- (f)
- if and only if ;
- (g)
- if and only if .
To prove the above theorem, we start with the following:
Lemma 2.
Let be an integer. Then,
Proof.
Clearly, , and . If , then the detour distance between any two vertices of is at least four. Therefore, . □
Proposition 4.
Let be an integer. Then,
- , , , , , and if and only if ;
- , , , if and only if ;
- if and only if .
Proof.
Clearly, . Note that and . Furthermore, if , then is connected and is -regular. Thus, the proof follows from Lemma 2. □
Proposition 5.
Let G be a graph.
- If G is connected non-unicyclic, then , ,, , ; , ,, and .
- If G is disconnected, then , and .
Proof.
- Let G be connected non-unicyclic. Suppose that . Then, we have , so G is unicyclic, since G is connected, which is a contradiction to our assumption that G is non-unicyclic. Thus, . The proof of the rest of the cases are similar to the above.
- Let G be disconnected. Then, , are disconnected and is connected. Combining these pieces of information, we get the result.
□
Proposition 6.
Let G be a connected unicyclic graph but not a cycle. Then,
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- ;
- .
Proof.
- By the structure of G, the graph is connected non-unicyclic. Let the maximum length among all the cycles in be k. Clearly, . If , then any vertex in such a cycle is isolated in . If , then , and , respectively. Thus, is disconnected and .
- By part (a), is disconnected. However, is connected except for the graph . Thus, . If , then has two isolated vertices. However, has exactly one isolated vertex. Therefore, .
- If or , , then is disconnected, so is disconnected. Thus, .If G is the graph other than these graphs, then the maximum length among all the cycles in is at least seven. Then, any vertex in such a cycle is isolated in . Thus, .
- By part (c), is disconnected. Therefore, the rest of the proof is similar to part (b).
- By part (a), is disconnected. Thus, is disconnected and so .
- (f)-
- The proof is similar to the proof of part (b), since , and
- (h):
- are disconnected.
- (i)-
- The proof of part (i) and (j) are similar to the proof of parts (c) and (d), respectively,
- (j):
- since is disconnected.
□
Combining Propositions 4–6, we get the proof of Theorem 2.
4. Solutions of Graph Equations of Detour Antipodal Graphs and Line Graphs
The main result on solving graph equations involving detour antipodal graphs we prove in this section is the following:
Theorem 3.
Let G be a graph. Then,
- if and only if for some ;
- if and only if ;
- if and only if for some ;
- if and only if ;
- if and only if ;
- if and only if ;
- if and only if .
- if and only if ;
- if and only if , where and n is odd;
- if and only if , where and n is odd;
- if and only if , where and ;
- if and only if , where and ;
- if and only if , where n is odd;
- if and only if ;
- if and only if ;
- if and only if ;
- if and only if .
- if and only if or ;
- if and only if ;
- if and only if ;
- if and only if , where and n is odd;
- if and only if , where , n is odd and ;
- if and only if , where n is odd;
- if and only if or ;
- if and only if or ;
- if and only if or .
Lemma 3.
Consider the graph , where and . Then,
- , where e is any edge in .
- .
- , if and .
Lemma 4.
Let be an integer. Then, .
Proof.
The proof follows directly from the definition of a detour antipodal graph. □
Proposition 7.
Let be an integer. Then,
- , , ,, if and only if .
- , , if and only if .
- , if and only if .
- , for all .
- , , if and only if and n is odd.
- , , if and only if , n is odd and .
- , if and only if .
- if and only if .
- if and only if .
Proof.
Clearly . Note that and . Furthermore, if , then is connected and is -regular. Thus, the proof follows from Lemmas 1, 2 and 4. □
Proposition 8.
Let G be either connected non-unicyclic or a disconnected graph. Then,
, , , , , , , , , , , , ,
, , , , , , , , , , , , .
Proof.
We need to consider the following cases.
Case (i): Let G be connected non-unicyclic. Suppose that . Then, we have , so G is connected and unicyclic, which is a contradiction to our assumption that G is non-unicyclic. Hence, . The proof of the rest of the cases are similar to the above.
Case (ii): Let G be disconnected. Then, , , , , , all are totally disconnected. is disconnected and and are connected. Combining all the information, we get the result.
The proof follows from the above cases. □
Proposition 9.
Let G be a connected unicyclic graph but not a cycle. Then,
- ;
- ;
- ;
- ;
- ; ; ; ;; ; ; ; ; ;
- ; ; ; ;;
- ; ; ; ; ;
- ; ;
- ; ; ;
- ; ; ; ; .
Proof.
- (1):
- Clearly, is connected. We show that is disconnected. Let . Then, there exist two vertices , in G such that . Since are at detour diametrical distance, at least one of them must be pendent; without loss of generality, we assume that is pendent. Let be a neighbor of in G. We claim that is an isolated vertex in . Suppose is adjacent to any vertex in , then . Thus, , which is a contradiction to our assumption that the detour diameter of G is k. Therefore, is an isolated vertex in . It follows that is disconnected. Thus, .
- (2):
- If , , then . If , , has exactly one pendent vertex. By Lemma 3 (ii), we have .If G is the graph other than these graphs, then by the argument of part (a), is disconnected. Thus, is connected. Hence, .
- (3):
- If , then has as a subgraph. Thus, .Now, we assume that G is non-isomorphic to the above-mentioned graph. Then, by the similar argument used in the proof of part (1), we get .
- (4):
- By part (3), is disconnected; but is connected. Hence .
- (5):
- By part (1), we have is disconnected. Thus, , , , and all are disconnected. However, G and are connected. Thus, none of the above graphs is isomorphic to G or .
- (6):
- By part (1) and Lemma 3, none of the graphs , , , and is isomorphic to .
- (7):
- If , then . Thus, and are totally disconnected. Hence, both and are not isomorphic to G. Furthermore, , and have either at least two cycles or a cycle as a proper subgraph. However, G is unicyclic. Hence, none of , and is isomorphic to G. By part (3), we have is disconnected. Thus, none of the graphs , , , and is isomorphic to G.
- (8):
- If , then as a subgraph.Thus, and are totally disconnected; however, is not totally disconnected. Thus, both and are not isomorphic to .By part (3), we have is disconnected. However, is connected. So both and are not isomorphic to .
- (9):
- If , , and are totally disconnected, since , and have no isolated vertices. However, has one isolated vertex. Thus, none of , , , and is isomorphic to .By part (3), we have is disconnected; however, is connected. Hence, none of , , , and is isomorphic to .
- (10):
- If or , , then has either two isolated vertices or exactly one isolated vertex. By Lemma 3, we have , , , and are not isomorphic to .If G is the graph other than these graphs, then by the argument of part (a), is disconnected. Thus, is connected. Hence, none of , , , and is isomorphic to .
□
Combining Propositions 7–9, we get the proof of Theorem 3.
5. Conclusions
Given a set of wireless sensor nodes and connections, graph theory provides a useful tool to simplify the many moving parts of dynamic systems. In this work, we mainly focused on the study of detour distance graph equations. In particular, we solved some graph equations involving detour two-distance graphs, detour three-distance graphs, detour antipodal graphs and line graphs. This solution is believed to be useful for many researchers and businesses working in wireless sensor networks.
Author Contributions
Conceptualization, S.C.P.; data curation, S.C.P. and M.P.; formal analysis, S.A.; funding acquisition, H.-K.S. and H.M.; investigation, W.C.; methodology, M.P. and N.A.; project administration, H.-K.S. and G.P.J.; resources, H.M.; software, N.A.; supervision, G.P.J. and H.M.; validation, W.C.; visualization, S.A.; writing—original draft, S.C.P.; writing— review and editing, G.P.J. All authors have read and agreed to the published version of the manuscript.
Funding
This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2020R1A6A1A03038540) and by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through the Digital Breeding Transformation Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) (322063-03-1-SB010) and by the Technology development Program (RS-2022-00156456) funded by the Ministry of SMEs and Startups (MSS, Korea).
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Acknowledgments
Anbazhagan and Amutha would like to thank RUSA Phase 2.0 (F 24-51/2014-U), DST-FIST (SR/FIST/MS-I/2018/17), DST-PURSE 2nd Phase programme (SR/PURSE Phase 2/38), Govt. of India.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Aigner, M. Graphs whose complement and line graph are isomorphic. J. Comb. Theory 1969, 7, 273–275. [Google Scholar] [CrossRef][Green Version]
- Azimi, A.; Farrokhi, M.F.D. Simple graphs whose 2-distance graphs are paths or cycles. Le Mathematiche 2014, 69, 183–191. [Google Scholar]
- Beineke, L.W. Characterizations of derived graphs. J. Comb. Theory 1970, 9, 129–135. [Google Scholar] [CrossRef]
- Bondy, J.A.; Murty, U.S.R. Graph Theory; Springer: Berlin/Heidelberg, Germany, 2008. [Google Scholar]
- Cvetkovic, D.M.; Lackovic, I.B.; Simic, S.K. Graph equations, graph inequalities and a fixed point theorem. Publ. Inst. Math. 1976, 20, 59–66. [Google Scholar]
- Cvetkovic, D.M.; Simic, S.K. A bibliography of graph equations. J. Graph Theory 1979, 3, 311–324. [Google Scholar] [CrossRef]
- Furediand, M.; Kang, J.H. Distance graphs on Zn with l1 norm. Theort. Comput. Sci. 2007, 319, 357–366. [Google Scholar] [CrossRef][Green Version]
- Hiroshi, S. On distance i graphs of distance regular graphs. Kyushu J. Math. 1994, 48, 379–408. [Google Scholar]
- Chen, J.-J.; Chang, X.J. Distance graphs on Rn with l1 norm. J. Comb. Optim. 2007, 14, 267–274. [Google Scholar] [CrossRef]
- Ching, R.P.; Garces, I.J.L. Characterizing 2-distance graphs and solving the equations T2(X)=kP2 or Km∪Kn. arXiv 2015, arXiv:1510.00924. [Google Scholar]
- Saravanakumar, S.; Nagarajan, K. Odd and even distance graphs. Int. J. Math. Soft Comput. 2015, 5, 93–103. [Google Scholar] [CrossRef]
- Simic, S.K. Graph equations for line graphs and n-distance graphs. Publications de l’Institut Mathématique 1983, 33, 203–216. [Google Scholar]
- Simic, S.K. Graph equation Ln(G)≅G¯. Ser. Math. Fiz. 1975, 498, 41–44. [Google Scholar]
- Whitney, H. Congruent graphs and connectivity of graphs. Amer. J. Math. 1932, 54, 150–168. [Google Scholar] [CrossRef]
- Al-Homidan, S.; Wolkowicz, H. Approximate and exact completion problems for Euclidean distance matrices using semidefinite programming. Linear Algebra Appl. 2005, 406, 109–141. [Google Scholar] [CrossRef][Green Version]
- Gower, J.C. Properties of Euclidean and non-Euclidean distance matrices. Linear Algebra Appl. 1985, 67, 81–97. [Google Scholar] [CrossRef]
- Menon, V. The isomorphism between graphs and their adjoint graphs. Canad. Math. Bull. 1965, 8, 7–15. [Google Scholar] [CrossRef]
- Rajkumar, R.; Prabha, S.C. Some results of solving n-distance Graph equations. Glob. J. Pure Appl. Math. 2017, 13, 178–184. [Google Scholar]
- Rajkumar, R.; Prabha, S.C. Solutions of some 3-distance graph equations. Glob. J. Pure Appl. Math. 2017, 13, 369–375. [Google Scholar]
- Rajkumar, R.; Prabha, S.C. Solutions of Some 2-Distance Graph Equations. Aip Conf. Proc. 2019, 2112, 020109. [Google Scholar] [CrossRef]
- Rajkumar, R.; Prabha, S.C. On characterization of distance graph of a path. Bull. Int. Math. Virtual Inst. 2018, 8, 315–323. [Google Scholar]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).