SlideShare a Scribd company logo
A.SARANYA ,
Assistant professor in Mathematics,
Sri Adi Chunchanagiri women's college,
Cumbum.
 History
 Definition of Graph
 Special Edges
 Types of Edges
 Representation of graphs
 Applications
The history of graph theory may be specifically traced to 1735, when the Swiss
mathematician Leonhard Euler solved the Königsberg bridge problem. The
Königsberg bridge problem was an old puzzle concerning the possibility of finding a
path over every one of seven bridges that span a forked river flowing past an
island—but without crossing any bridge twice. Euler argued that no such path
exists. His proof involved only references to the physical arrangement of the
bridges, but essentially he proved the first theorem in graph theory.
Definition of graph
It is a pair G=(V,E)
where,
V=V(G) = set of vertices
E=E(G)=set of edges
Example:
In the above graph,(right side)
V={A,B,C,D,E}
E={{A,B),(A,C),(C,D),(D,E),(B,D}
Parallel Edges
Two or more edges joining a pair of vertices
In the example, a and b are joined by two parallell
Edges
Loops
An edge that starts and ends at the same vertex.
In the example, vertex d has a loop
Graph can be of two types based upon the type of edges:
i. Directed Edges:
Here the arcs between two vertices have a particular direction; they are directed from one
vertex to another. It is usually represented by an arrow
ii. Undirected Edges:
Here the edges do not have any particular direction from one vertex to another; there is no
difference between the two vertices connected via one undirected edge. It is usually
represented by a straight line.
A graph can be represented mainly as two ways:
i. Adjacency matrices.
ii. Adjacency lists.
i. Adjacency Matrices:
Here the graph is represented as an n × n square matrix; M.
n represents the number of vertices present in the graph.
If Mij = 1, it means there is an edge connecting vertex i and vertex j and if Mij = 0,
it means there is no edge connecting vertex i and vertex j.
Let us consider the following 6x6 matrix
Adjacency matrix and its corresponding graphs
Although the computation process in adjacency matrix is quite simple but it
contains lots of zeroes and wastes a lots of space. In adjacency list representation of
graphs, this disadvantage has been eliminated.
ii. Adjacency list:
In this case, all the zeroes of the adjacency matrix are eliminated and only the
corresponding neighboring nodes of a particular node are considered.
Neighboring nodes of 1: 2, 5.
Neighboring nodes of 2: 1, 3, and 5.
Neighboring nodes of 3: 2, 4.
Neighboring nodes of 4: 3, 5, and 6.
Neighboring nodes of 5: 1, 2, and 4.
Neighboring nodes of 6: 4.
Adjacency list and its corresponding matrix
Here, in adjacency list, all the zeroes of the adjacency matrix are eliminated and the
wastage of space is also being reduced. But the complexity in computation increases
in this case.
Computer Science
 Graphs are used to define the flow of computation.
 Graphs are used to represent networks of communication.
 Graphs are used to represent data organization.
 Graph transformation systems work on rule-based in-memory manipulation of graphs.
Graph databases ensure transaction-safe, persistent storing and querying of graph
structured data.
 Graph theory is used to find shortest path in road or a network.
 In Google Maps, various locations are represented as vertices or nodes and the roads are
represented as edges and graph theory is used to find the shortest path between two nodes.
Physics and Chemistry
 In physics and chemistry, graph theory is used to study molecules.
 The 3D structure of complicated simulated atomic structures can be studied quantitatively
by gathering statistics on graph-theoretic properties related to the topology of the atoms.
 Statistical physics also uses graphs. In this field graphs can represent local connections
between interacting parts of a system, as well as the dynamics of a physical process on
such systems.
 Graphs are also used to express the micro-scale channels of porous media, in which the
vertices represent the pores and the edges represent the smaller channels connecting the
pores.
 Graph is also helpful in constructing the molecular structure as well as lattice of the
molecule. It also helps us to show the bond relation in between atoms and molecules, also
help in comparing structure of one molecule to other.
Computer Network
 In computer network, the relationships among interconnected computers within the
network, follow the principles of graph theory.
 Graph theory is also used in network security.
 We can use the vertex coloring algorithm to find a proper coloring of the map with four
colors.
 Vertex coloring algorithm may be used for assigning at most four different frequencies for
any GSM (Grouped Special Mobile) mobile phone networks.

More Related Content

Similar to Graph theory ppt.pptx

CONTENTS (1) (1).pdf
CONTENTS (1) (1).pdfCONTENTS (1) (1).pdf
CONTENTS (1) (1).pdf
RahulMeena399479
 
A glimpse to topological graph theory
A glimpse to topological graph theoryA glimpse to topological graph theory
A glimpse to topological graph theory
ANJU123MOHANAN
 
gsm nithya.pdf
gsm nithya.pdfgsm nithya.pdf
gsm nithya.pdf
mathematicssac
 
Introduction to graph theory (All chapter)
Introduction to graph theory (All chapter)Introduction to graph theory (All chapter)
Introduction to graph theory (All chapter)
sobia1122
 
A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...
A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...
A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...
IRJET Journal
 
Graph: Euler path and Euler circuit
Graph: Euler path and Euler circuitGraph: Euler path and Euler circuit
Graph: Euler path and Euler circuit
Liwayway Memije-Cruz
 
Lecture 5b graphs and hashing
Lecture 5b graphs and hashingLecture 5b graphs and hashing
Lecture 5b graphs and hashingVictor Palmar
 
Graph Theory
Graph TheoryGraph Theory
Graph Theory
kailash shaw
 
Slides Chapter10.1 10.2
Slides Chapter10.1 10.2Slides Chapter10.1 10.2
Slides Chapter10.1 10.2showslidedump
 
Map Coloring and Some of Its Applications
Map Coloring and Some of Its Applications Map Coloring and Some of Its Applications
Map Coloring and Some of Its Applications
MD SHAH ALAM
 
APPLICATIONS OF GRAPH THEORY IN HUMAN LIFE
APPLICATIONS OF GRAPH THEORY IN HUMAN LIFEAPPLICATIONS OF GRAPH THEORY IN HUMAN LIFE
APPLICATIONS OF GRAPH THEORY IN HUMAN LIFE
Mary Calkins
 
Discrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part IDiscrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part IWongyos Keardsri
 
nossi ch 6
nossi ch 6nossi ch 6
nossi ch 6
lesaturner
 
Cs6702 graph theory and applications Anna University question paper apr may 2...
Cs6702 graph theory and applications Anna University question paper apr may 2...Cs6702 graph theory and applications Anna University question paper apr may 2...
Cs6702 graph theory and applications Anna University question paper apr may 2...
appasami
 
Entropy based measures for graphs
Entropy based measures for graphsEntropy based measures for graphs
Entropy based measures for graphs
Giorgos Bamparopoulos
 
Graph theory introduction - Samy
Graph theory  introduction - SamyGraph theory  introduction - Samy
Graph theory introduction - Samy
Mark Arokiasamy
 
matrices-1.pdf
matrices-1.pdfmatrices-1.pdf
matrices-1.pdf
WunnamAlabani
 
Graphs data structures
Graphs data structuresGraphs data structures
Graphs data structures
Jasleen Kaur (Chandigarh University)
 

Similar to Graph theory ppt.pptx (20)

CONTENTS (1) (1).pdf
CONTENTS (1) (1).pdfCONTENTS (1) (1).pdf
CONTENTS (1) (1).pdf
 
A glimpse to topological graph theory
A glimpse to topological graph theoryA glimpse to topological graph theory
A glimpse to topological graph theory
 
gsm nithya.pdf
gsm nithya.pdfgsm nithya.pdf
gsm nithya.pdf
 
Introduction to graph theory (All chapter)
Introduction to graph theory (All chapter)Introduction to graph theory (All chapter)
Introduction to graph theory (All chapter)
 
A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...
A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...
A MATLAB Computational Investigation of the Jordan Canonical Form of a Class ...
 
Graph: Euler path and Euler circuit
Graph: Euler path and Euler circuitGraph: Euler path and Euler circuit
Graph: Euler path and Euler circuit
 
Lecture 5b graphs and hashing
Lecture 5b graphs and hashingLecture 5b graphs and hashing
Lecture 5b graphs and hashing
 
26 spanning
26 spanning26 spanning
26 spanning
 
Graph Theory
Graph TheoryGraph Theory
Graph Theory
 
Slides Chapter10.1 10.2
Slides Chapter10.1 10.2Slides Chapter10.1 10.2
Slides Chapter10.1 10.2
 
Map Coloring and Some of Its Applications
Map Coloring and Some of Its Applications Map Coloring and Some of Its Applications
Map Coloring and Some of Its Applications
 
APPLICATIONS OF GRAPH THEORY IN HUMAN LIFE
APPLICATIONS OF GRAPH THEORY IN HUMAN LIFEAPPLICATIONS OF GRAPH THEORY IN HUMAN LIFE
APPLICATIONS OF GRAPH THEORY IN HUMAN LIFE
 
Discrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part IDiscrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part I
 
nossi ch 6
nossi ch 6nossi ch 6
nossi ch 6
 
Cs6702 graph theory and applications Anna University question paper apr may 2...
Cs6702 graph theory and applications Anna University question paper apr may 2...Cs6702 graph theory and applications Anna University question paper apr may 2...
Cs6702 graph theory and applications Anna University question paper apr may 2...
 
Entropy based measures for graphs
Entropy based measures for graphsEntropy based measures for graphs
Entropy based measures for graphs
 
Graph theory introduction - Samy
Graph theory  introduction - SamyGraph theory  introduction - Samy
Graph theory introduction - Samy
 
graphs
graphsgraphs
graphs
 
matrices-1.pdf
matrices-1.pdfmatrices-1.pdf
matrices-1.pdf
 
Graphs data structures
Graphs data structuresGraphs data structures
Graphs data structures
 

Recently uploaded

Model Attribute Check Company Auto Property
Model Attribute  Check Company Auto PropertyModel Attribute  Check Company Auto Property
Model Attribute Check Company Auto Property
Celine George
 
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
siemaillard
 
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup   New Member Orientation and Q&A (May 2024).pdfWelcome to TechSoup   New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
TechSoup
 
Embracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic ImperativeEmbracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic Imperative
Peter Windle
 
Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345
beazzy04
 
The Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdfThe Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdf
kaushalkr1407
 
How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...
Jisc
 
A Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in EducationA Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in Education
Peter Windle
 
Synthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptxSynthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptx
Pavel ( NSTU)
 
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXXPhrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
MIRIAMSALINAS13
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
MysoreMuleSoftMeetup
 
Overview on Edible Vaccine: Pros & Cons with Mechanism
Overview on Edible Vaccine: Pros & Cons with MechanismOverview on Edible Vaccine: Pros & Cons with Mechanism
Overview on Edible Vaccine: Pros & Cons with Mechanism
DeeptiGupta154
 
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdfAdversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Po-Chuan Chen
 
Thesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.pptThesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.ppt
EverAndrsGuerraGuerr
 
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCECLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
BhavyaRajput3
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
Ashokrao Mane college of Pharmacy Peth-Vadgaon
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
TechSoup
 
Language Across the Curriculm LAC B.Ed.
Language Across the  Curriculm LAC B.Ed.Language Across the  Curriculm LAC B.Ed.
Language Across the Curriculm LAC B.Ed.
Atul Kumar Singh
 
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxChapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
Mohd Adib Abd Muin, Senior Lecturer at Universiti Utara Malaysia
 
The French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free downloadThe French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free download
Vivekanand Anglo Vedic Academy
 

Recently uploaded (20)

Model Attribute Check Company Auto Property
Model Attribute  Check Company Auto PropertyModel Attribute  Check Company Auto Property
Model Attribute Check Company Auto Property
 
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa
 
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup   New Member Orientation and Q&A (May 2024).pdfWelcome to TechSoup   New Member Orientation and Q&A (May 2024).pdf
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdf
 
Embracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic ImperativeEmbracing GenAI - A Strategic Imperative
Embracing GenAI - A Strategic Imperative
 
Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345Sha'Carri Richardson Presentation 202345
Sha'Carri Richardson Presentation 202345
 
The Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdfThe Roman Empire A Historical Colossus.pdf
The Roman Empire A Historical Colossus.pdf
 
How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...How libraries can support authors with open access requirements for UKRI fund...
How libraries can support authors with open access requirements for UKRI fund...
 
A Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in EducationA Strategic Approach: GenAI in Education
A Strategic Approach: GenAI in Education
 
Synthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptxSynthetic Fiber Construction in lab .pptx
Synthetic Fiber Construction in lab .pptx
 
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXXPhrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
Phrasal Verbs.XXXXXXXXXXXXXXXXXXXXXXXXXX
 
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
 
Overview on Edible Vaccine: Pros & Cons with Mechanism
Overview on Edible Vaccine: Pros & Cons with MechanismOverview on Edible Vaccine: Pros & Cons with Mechanism
Overview on Edible Vaccine: Pros & Cons with Mechanism
 
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdfAdversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
 
Thesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.pptThesis Statement for students diagnonsed withADHD.ppt
Thesis Statement for students diagnonsed withADHD.ppt
 
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCECLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
 
Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.Biological Screening of Herbal Drugs in detailed.
Biological Screening of Herbal Drugs in detailed.
 
Introduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp NetworkIntroduction to AI for Nonprofits with Tapp Network
Introduction to AI for Nonprofits with Tapp Network
 
Language Across the Curriculm LAC B.Ed.
Language Across the  Curriculm LAC B.Ed.Language Across the  Curriculm LAC B.Ed.
Language Across the Curriculm LAC B.Ed.
 
Chapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptxChapter 3 - Islamic Banking Products and Services.pptx
Chapter 3 - Islamic Banking Products and Services.pptx
 
The French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free downloadThe French Revolution Class 9 Study Material pdf free download
The French Revolution Class 9 Study Material pdf free download
 

Graph theory ppt.pptx

  • 1. A.SARANYA , Assistant professor in Mathematics, Sri Adi Chunchanagiri women's college, Cumbum.
  • 2.  History  Definition of Graph  Special Edges  Types of Edges  Representation of graphs  Applications
  • 3. The history of graph theory may be specifically traced to 1735, when the Swiss mathematician Leonhard Euler solved the Königsberg bridge problem. The Königsberg bridge problem was an old puzzle concerning the possibility of finding a path over every one of seven bridges that span a forked river flowing past an island—but without crossing any bridge twice. Euler argued that no such path exists. His proof involved only references to the physical arrangement of the bridges, but essentially he proved the first theorem in graph theory.
  • 4. Definition of graph It is a pair G=(V,E) where, V=V(G) = set of vertices E=E(G)=set of edges Example: In the above graph,(right side) V={A,B,C,D,E} E={{A,B),(A,C),(C,D),(D,E),(B,D}
  • 5. Parallel Edges Two or more edges joining a pair of vertices In the example, a and b are joined by two parallell Edges Loops An edge that starts and ends at the same vertex. In the example, vertex d has a loop
  • 6. Graph can be of two types based upon the type of edges: i. Directed Edges: Here the arcs between two vertices have a particular direction; they are directed from one vertex to another. It is usually represented by an arrow ii. Undirected Edges: Here the edges do not have any particular direction from one vertex to another; there is no difference between the two vertices connected via one undirected edge. It is usually represented by a straight line.
  • 7. A graph can be represented mainly as two ways: i. Adjacency matrices. ii. Adjacency lists. i. Adjacency Matrices: Here the graph is represented as an n × n square matrix; M. n represents the number of vertices present in the graph. If Mij = 1, it means there is an edge connecting vertex i and vertex j and if Mij = 0, it means there is no edge connecting vertex i and vertex j. Let us consider the following 6x6 matrix
  • 8. Adjacency matrix and its corresponding graphs
  • 9. Although the computation process in adjacency matrix is quite simple but it contains lots of zeroes and wastes a lots of space. In adjacency list representation of graphs, this disadvantage has been eliminated. ii. Adjacency list: In this case, all the zeroes of the adjacency matrix are eliminated and only the corresponding neighboring nodes of a particular node are considered.
  • 10. Neighboring nodes of 1: 2, 5. Neighboring nodes of 2: 1, 3, and 5. Neighboring nodes of 3: 2, 4. Neighboring nodes of 4: 3, 5, and 6. Neighboring nodes of 5: 1, 2, and 4. Neighboring nodes of 6: 4.
  • 11. Adjacency list and its corresponding matrix Here, in adjacency list, all the zeroes of the adjacency matrix are eliminated and the wastage of space is also being reduced. But the complexity in computation increases in this case.
  • 12. Computer Science  Graphs are used to define the flow of computation.  Graphs are used to represent networks of communication.  Graphs are used to represent data organization.  Graph transformation systems work on rule-based in-memory manipulation of graphs. Graph databases ensure transaction-safe, persistent storing and querying of graph structured data.  Graph theory is used to find shortest path in road or a network.  In Google Maps, various locations are represented as vertices or nodes and the roads are represented as edges and graph theory is used to find the shortest path between two nodes.
  • 13. Physics and Chemistry  In physics and chemistry, graph theory is used to study molecules.  The 3D structure of complicated simulated atomic structures can be studied quantitatively by gathering statistics on graph-theoretic properties related to the topology of the atoms.  Statistical physics also uses graphs. In this field graphs can represent local connections between interacting parts of a system, as well as the dynamics of a physical process on such systems.  Graphs are also used to express the micro-scale channels of porous media, in which the vertices represent the pores and the edges represent the smaller channels connecting the pores.
  • 14.  Graph is also helpful in constructing the molecular structure as well as lattice of the molecule. It also helps us to show the bond relation in between atoms and molecules, also help in comparing structure of one molecule to other. Computer Network  In computer network, the relationships among interconnected computers within the network, follow the principles of graph theory.  Graph theory is also used in network security.  We can use the vertex coloring algorithm to find a proper coloring of the map with four colors.  Vertex coloring algorithm may be used for assigning at most four different frequencies for any GSM (Grouped Special Mobile) mobile phone networks.