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Application of Graph Theory in Computer Science and Engineering

Dr. Vasanthakumari T.N.

Assistant Professor

Department of Mathematics

Government First Grade College, Tumakuru, Karnataka


ABSTRACT

The field of mathematics plays vital role in various fields. One of the important areas in mathematics is graph theory which is used in structural models. This structural arrangements of various objects or technologies lead to new inventions and modifications in the existing environment for enhancement in many fields. The field graph theory started its journey from the problem of Koinsberg Bridge in 1735. This paper gives an overview of the applications of graph theory in many different fields to some extent but mainly focuses on the computer science applications that uses graph theoretical concepts. Various papers and related works based on graph theory have been studied and implemented for this scheduled concepts, computer science applications.

KEY WORDS: Graph Theory, Koinsberg Bridge, mathematical structures, Data base design

INTRODUCTION

Graph theory is a branch of discrete mathematics. In mathematics and computer science, graph theory is the study of graphs which are mathematical structures used to model pair wise relations between objects. There is wide use of graphs in providing problem solving techniques, because it gives an intuitive manner prior to presenting formal definition. To analyze the graph theory application two problem areas are considered.

  1. Classical problem
  2.  Problems from applications.

The classical problem are defined with the help of the graph theory as connectivity, cuts, paths and flows, coloring problems and theoretical aspect of graph drawing. Whereas problems from application particularly emphasis on experimental research and the implementation of the graph theory algorithms. Graph drawing is a key topic in implementation point of view, because the automatic generation of drawing graph has important applications in key computer science technologies such as data base design, software engineering, circuit designing, network designing and visual interfaces.

APPLICATION IN COMPUTER SCIENCE:

Data base designing:

In data base designing graphs are used as graph data bases. Graph database uses graph representation with nodes, edges, and properties to represent and store data. This graph structure has key role in designing database, because it gives fast implementation process using different functionality and properties of graph structure .Graph database uses as:

  • Storage system that provides index free adjacency. 
  • Analyzing tool for interconnection.
  • Powerful tool for graph like-query.
  • Graph databases are often faster for associative data sets that map more directly to the structure of object-oriented applications.

Software engineering:

Graph has many applications in software engineering. For example: during Requirements Specification, Data Flow diagrams are used where vertices represent transformations and edges represents the data flows. During Design phase, graphical design is used for describing relations among modules; while during Testing, the control flow of a program associated with McCabe's complexity measure which employs directed graphs for addressing the sequence of executed instructions and etc. Even Software Process Management has also applications of network diagrams which involves graph algorithms.

Network system:

Graph theory has wide application in the field of networking. To analyze the graph theory application in networking two areas are considered: graph based representation and network theory. Graph based representation has many advantages such as it gives different point of view; it makes problem much easier and provide more accurate definition. Whereas network theory provide a set of techniques for analyzing a graph and applying network theory using a graph representation. The term graph and network are equal. Both refer to a type of structure in which there exists vertices (i.e. nodes, dots) and edges (i.e. links, lines). There are numerous types of graphs and networks which yield more or less structure. These two terms can be differentiating on the basis of their utility.

Data structure:

Data may be organized many different ways. The logical or mathematical model of a particular organization of data is called a “data structure”. The choice of data model depends on two considerations:

  • It must be rich enough in structure to mirror actual relationship of data in real world.  The structure should be simple enough that one can
  • effectively process data when necessary

These two considerations is fulfilled by the graph theoretical concepts. Arbitrary relation among data can also be represented by a graph and its matrices , operations performed on these metrics are further useful for deriving relations and data association and is useful in order to understand how these data may be stored in memory.

Conclusion:

 The fundamental rationale of this paper is to present the significance of the graph theoretical thoughts in various fields of computer applications for exploring that they can utilize graph theoretical concepts for the examination. An outline is exhibited particularly to extend graph theory. Analysts may make them inspire data to graph theory and its applications in the computer field and get a few contemplations identified with their territory of research.

Bibliography

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  2. Anindya J.Pal, Samar S.Sarma, Biman Ray, “CCTP, Graph Coloring algorithms – Soft computing Solutions IEEE, 2007
  3. Bing Hong Liu, Wel Chieh Ke, Chin-Hsien Tsai, Ming-Jer Tsai, “Constructing a message pruning tree with minimum cost for tracking moving objects in wireless sensor networks”, IEEE Volume 57, Number 6, July 2008
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  5. Gian Luca Marcialis, Fabio Roli, Alessandra Serrau, “Graph Based and Structural Methods for Fingerprint Classification, Springer verlag, Berlin Heidelberg 2007
  6. John.P.Hayes, “A graph Model for Fault Tolerant Computing Systems”, IEEE September 1976
  7. Narasingh Deo, “Graph theory with applications to engineering and computer science”, Prentice Hall of India, 1990.
  8. Perri Mehonen, Janne Riihijarvi, Marina Petrova, “Automatic Channel allocation for small wireless area networks using graph coloring algorithm approach”, IEEE 2004

References

  1. F.R.K. Chung and L. Lu. Complex Graphs and Networks, volume 107 of CBMS Regional Conference Series in Mathematics. American Mathematical Society, 2006.
  2. Y. Breitbart, M. Garofalakis, C. Martin, R. Rastogi, S. Seshadri and A. Silberschatz. “ Topology Discovery in Heterogeneous IP Networks” In Proceedings of IEEE INFOCOM, 2000.
  3. H. Gobjuka and Y. Breitbart. Ethernet topology discovery for networks with incomplete information. In IEEE/ACM Transactions in Networking, pages 18:1220–1233, 2010.
  4. Saleh Ali K. Al Omari and Putra Sumari, “ An overview of Mobile Ad Hoc Networks for the existing protocols and applications”, International Journal on applications of graph theory in wireless ad hoc networks and sensor networks, vol. 2, no. 1, March 2010.
  5. K. Ahmat, Ethernet Topology Discovery: A Survey," CoRR, vol. abs/0907.3095, 2009.
  6. K. Ahmat, Graph Theory and Optimization Problems for Very Large Networks. City University of New York, United States, 2009
  7. S. Sumathy et. al. ,”Secure key exchange and encryption mechanism for group communication in wireless ad hoc networks ”, Journal on Applications of graph theory in wireless ad hoc networks and sensor networks, Vol 2,No 1,March 2010.


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