A Parallel Genetic Algorithm for Shortest Path Routing Problem

Author

Yussof, Salman ; Razali, Rina Azlin ; See, Ong Hang

fYear

2009

fDate

3-5 April 2009

Firstpage

268

Lastpage

273

Abstract

Shortest path routing is the type of routing widely used in computer networks nowadays. Even though shortest path routing algorithms are well established, other alternative methods may have their own advantages. One such alternative is to use a GA-based routing algorithm. Based on previous research, GA-based routing algorithm has been found to be more scalable and insensitive to variations in network topologies. However, it is also known that GA-based routing algorithm is not fast enough for real-time computation. In this paper, we proposed a parallel genetic algorithm for solving the shortest path routing problem with the aim to reduce its computation time. This algorithm is developed and run on an MPI cluster. Based on experimental result, there is a tradeoff between computation time and the result accuracy. However, for the same level of accuracy, the proposed parallel algorithm can perform much faster compared to its non-parallel counterpart.

Keywords

application program interfaces; computer networks; genetic algorithms; parallel algorithms; telecommunication network routing; telecommunication network topology; MPI cluster; computer networks; message passing interface; network topology; parallel genetic algorithm; shortest path routing problem; Biological cells; Clustering algorithms; Computer networks; Concurrent computing; Electronic mail; Genetic algorithms; Genetic mutations; Message passing; Network topology; Routing; Coarse grained; message passing interface; parallel genetic algorithm; shortest path routing;

fLanguage

English

Publisher

ieee

Conference_Titel

Future Computer and Communication, 2009. ICFCC 2009. International Conference on

Conference_Location

Kuala Lumpar

Print_ISBN

978-0-7695-3591-3

Type

conf

DOI

10.1109/ICFCC.2009.36

Filename

5189787