• Title/Summary/Keyword: join of graphs

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On the Seidel Laplacian and Seidel Signless Laplacian Polynomials of Graphs

  • Ramane, Harishchandra S.;Ashoka, K.;Patil, Daneshwari;Parvathalu, B.
    • Kyungpook Mathematical Journal
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    • v.61 no.1
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    • pp.155-168
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    • 2021
  • We express the Seidel Laplacian polynomial and Seidel signless Laplacian polynomial of a graph in terms of the Seidel polynomials of induced subgraphs. Further, we determine the Seidel Laplacian polynomial and Seidel signless Laplacian polynomial of the join of regular graphs.

THE SPECTRAL DETERMINATIONS OF THE JOIN OF TWO FRIENDSHIP GRAPHS

  • Abdian, Ali Zeydi;Moez, Amirhossein Morovati
    • Honam Mathematical Journal
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    • v.41 no.1
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    • pp.67-87
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    • 2019
  • The main aim of this study is to characterize new classes of multicone graphs which are determined by their adjacency spectra, their Laplacian spectra, their complement with respect to signless Laplacian spectra and their complement with respect to their adjacency spectra. A multicone graph is defined to be the join of a clique and a regular graph. If n is a positive integer, a friendship graph $F_n$ consists of n edge-disjoint triangles that all of them meet in one vertex. It is proved that any connected graph cospectral to a multicone graph $F_n{\nabla}F_n=K_2{\nabla}nK_2{\nabla}nK_2$ is determined by its adjacency spectra as well as its Laplacian spectra. In addition, we show that if $n{\neq}2$, the complement of these graphs are determined by their adjacency spectra. At the end of the paper, it is proved that multicone graphs $F_n{\nabla}F_n=K_2{\nabla}nK_2{\nabla}nK_2$ are determined by their signless Laplacian spectra and also we prove that any graph cospectral to one of multicone graphs $F_n{\nabla}F_n$ is perfect.

ON THE FIXING NUMBER OF FUNCTIGRAPHS

  • Fazil, Muhammad;Javaid, Imran;Murtaza, Muhammad
    • Bulletin of the Korean Mathematical Society
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    • v.58 no.1
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    • pp.171-181
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    • 2021
  • The fixing number of a graph G is the smallest order of a subset S of its vertex set V (G) such that the stabilizer of S in G, ��S(G) is trivial. Let G1 and G2 be the disjoint copies of a graph G, and let g : V (G1) → V (G2) be a function. A functigraph FG consists of the vertex set V (G1) ∪ V (G2) and the edge set E(G1) ∪ E(G2) ∪ {uv : v = g(u)}. In this paper, we study the behavior of fixing number in passing from G to FG and find its sharp lower and upper bounds. We also study the fixing number of functigraphs of some well known families of graphs like complete graphs, trees and join graphs.

ON CO-WELL COVERED GRAPHS

  • Abughazaleh, Baha';Abughneim, Omar;Al-Ezeh, Hasan
    • Communications of the Korean Mathematical Society
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    • v.35 no.2
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    • pp.359-370
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    • 2020
  • A graph G is called a well covered graph if every maximal independent set in G is maximum, and co-well covered graph if its complement is a well covered graph. We study some properties of a co-well covered graph and we characterize when the join, the corona product, and cartesian product are co-well covered graphs. Also we characterize when powers of trees and cycles are co-well covered graphs. The line graph of a graph which is co-well covered is also studied.

An Effective Algorithm for Constructing the Dominator Tree from Irreducible Directed Graphs (감축 불가능한 유향그래프로부터 지배자 트리를 구성하기 위한 효과적인 알고리즘)

  • Lee, Dae-Sik;Sim, Son-Kweon;Ahn, Heui-Hak
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.8
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    • pp.2536-2542
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    • 2000
  • The dominator tree presents the dominance frontier from directed graph to the tree. we present the effective algorithm for constructing the dominator tree from arbitrarY directed graph. The reducible flow graph was reduced to dominator tree after dominator calculation. And the irreducible flow graph was constructed to dominator-join graph using join-edge information of information table. For reducing the dominator tree from dominator-join graph, we present the effective sequency reducible algorithm and delay reducible algorithm.

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L(4, 3, 2, 1)-PATH COLORING OF CERTAIN CLASSES OF GRAPHS

  • DHANYASHREE;K.N. MEERA
    • Journal of applied mathematics & informatics
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    • v.41 no.3
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    • pp.511-524
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    • 2023
  • An L(p1, p2, p3, . . . , pm)-labeling of a graph G is an assignment of non-negative integers, called as labels, to the vertices such that the vertices at distance i should have at least pi as their label difference. If p1 = 4, p2 = 3, p3 = 2, p4 = 1, then it is called a L(4, 3, 2, 1)-labeling which is widely studied in the literature. A L(4, 3, 2, 1)-path coloring of graphs, is a labeling g : V (G) → Z+ such that there exists at least one path P between every pair of vertices in which the labeling restricted to this path is a L(4, 3, 2, 1)-labeling. This concept was defined and results for some simple graphs were obtained by the same authors in an earlier article. In this article, we study the concept of L(4, 3, 2, 1)-path coloring for complete bipartite graphs, 2-edge connected split graph, Cartesian product and join of two graphs and prove an existence theorem for the same.

TOTAL MEAN CORDIAL LABELING OF SOME CYCLE RELATED GRAPHS

  • Ponraj, R.;Narayanan, S. Sathish
    • Journal of applied mathematics & informatics
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    • v.33 no.1_2
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    • pp.101-110
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    • 2015
  • A Total Mean Cordial labeling of a graph G = (V, E) is a function $f:V(G){\rightarrow}\{0,1,2\}$ such that $f(xy)={\Large\lceil}\frac{f(x)+f(y)}{2}{\Large\rceil}$ where $x,y{\in}V(G)$, $xy{\in}E(G)$, and the total number of 0, 1 and 2 are balanced. That is ${\mid}ev_f(i)-ev_f(j){\mid}{\leq}1$, $i,j{\in}\{0,1,2\}$ where $ev_f(x)$ denotes the total number of vertices and edges labeled with x (x = 0, 1, 2). If there is a total mean cordial labeling on a graph G, then we will call G is Total Mean Cordial. Here, We investigate the Total Mean Cordial labeling behaviour of prism, gear, helms.

Development of Database Supported Graph Library and Graph Algorithms (데이터베이스에 기반한 그래프 라이브러리 및 그래프 알고리즘 개발)

  • 박휴찬;추인경
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.5
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    • pp.653-660
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    • 2002
  • This paper proposes a method for storing graphs and defining graph algorithms based on the well-developed relational database. In this method, graphs are represented in the form of relations. Each vertex and edge of a graph is represented as tuples of the table and saved in a database. We developed a library of graph operations for the storage and management of graphs and the development of graph applications. Furthermore, we defined graph algorithms in terms of relational algebraic operations such as projection, selection, and join. They can be implemented with the database language such as SQL. This database approach provides an efficient methodology to deal with very large-scale graphs and to support the development of graph applications.

MULTIPLICATIVELY WEIGHTED HARARY INDICES OF GRAPH OPERATIONS

  • Pattabiraman, K.
    • Journal of applied mathematics & informatics
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    • v.33 no.1_2
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    • pp.89-100
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    • 2015
  • In this paper, we present exact formulae for the multiplicatively weighted Harary indices of join, tensor product and strong product of graphs in terms of other graph invariants including the Harary index, Zagreb indices and Zagreb coindices. Finally, We apply our result to compute the multiplicatively weighted Harary indices of fan graph, wheel graph and closed fence graph.

Representation and Implementation of Graph Algorithms based on Relational Database (관계형 데이타베이스에 기반한 그래프 알고리즘의 표현과 구현)

  • Park, Hyu-Chan
    • Journal of KIISE:Databases
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    • v.29 no.5
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    • pp.347-357
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    • 2002
  • Graphs have provided a powerful methodology to solve a lot of real-world problems, and therefore there have been many proposals on the graph representations and algorithms. But, because most of them considered only memory-based graphs, there are still difficulties to apply them to large-scale problems. To cope with the difficulties, this paper proposes a graph representation and graph algorithms based on the well-developed relational database theory. Graphs are represented in the form of relations which can be visualized as relational tables. Each vertex and edge of a graph is represented as a tuple in the tables. Graph algorithms are also defined in terms of relational algebraic operations such as projection, selection, and join. They can be implemented with the database language such as SQL. We also developed a library of basic graph operations for the management of graphs and the development of graph applications. This database approach provides an efficient methodology to deal with very large- scale graphs, and the graph library supports the development of graph applications. Furthermore, it has many advantages such as the concurrent graph sharing among users by virtue of the capability of database.