Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

Nowadays, there are a lot of applications that affect the speedup of a computer which reduce its performance. High-performance computer is important because it is implemented in sectors where distributed parallel computing is needed to solve large scientific problems such as storing and processing l...

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Main Author:	Che Ibrahim, Mohd Erman Safawie
Format:	Thesis
Language:	English
Published:	2012
Subjects:	Fuzzy arithmetic Fuzzy logic
Online Access:	https://ir.uitm.edu.my/id/eprint/35330/1/35330.pdf
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id	my-uitm-ir.35330
record_format	uketd_dc
spelling	my-uitm-ir.353302020-10-20T04:59:25Z Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim 2012 Che Ibrahim, Mohd Erman Safawie Fuzzy arithmetic Evolutionary programming (Computer science). Genetic algorithms Fuzzy logic Nowadays, there are a lot of applications that affect the speedup of a computer which reduce its performance. High-performance computer is important because it is implemented in sectors where distributed parallel computing is needed to solve large scientific problems such as storing and processing large amounts of data. This project focuses on step-up cluster computing and a parallel Genetic Algorithm. The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. This project has the capability to reduce the execution time of application problem using parallel algorithms to increase efficiency of cluster computing. As a result, the network system successfully set-up by clustering computer that named Beowulf clusters and the application problem can be tested on this set-up to show that an increase in processing efficiency by manipulating the reduced communication latency among processors or compute nodes. This project recommended that the efficiency of the algorithm can also be improved by dynamically varying the set-up with other more powerful processor, more main memory capacity as well as faster interconnects. Hopefully, that this project will give benefits to all students and lectures to do the right research direction and fortunately this will provide future research work with ample room for problem testing and measurement of parallel processing 2012 Thesis https://ir.uitm.edu.my/id/eprint/35330/ https://ir.uitm.edu.my/id/eprint/35330/1/35330.pdf text en public degree Universiti Teknologi MARA Terengganu Faculty of Computer & Mathematical Sciences Mohamed Said, Mohamed Faidz
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Mohamed Said, Mohamed Faidz
topic	Fuzzy arithmetic Fuzzy arithmetic Fuzzy logic
spellingShingle	Fuzzy arithmetic Fuzzy arithmetic Fuzzy logic Che Ibrahim, Mohd Erman Safawie Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
description	Nowadays, there are a lot of applications that affect the speedup of a computer which reduce its performance. High-performance computer is important because it is implemented in sectors where distributed parallel computing is needed to solve large scientific problems such as storing and processing large amounts of data. This project focuses on step-up cluster computing and a parallel Genetic Algorithm. The objectives of this project to set-up Beowulf cluster computer to apply the Travelling Salesman Problem in parallel by using Genetic Algorithms and evaluate sequential algorithms and parallel algorithms by Genetic Algorithms. This project has the capability to reduce the execution time of application problem using parallel algorithms to increase efficiency of cluster computing. As a result, the network system successfully set-up by clustering computer that named Beowulf clusters and the application problem can be tested on this set-up to show that an increase in processing efficiency by manipulating the reduced communication latency among processors or compute nodes. This project recommended that the efficiency of the algorithm can also be improved by dynamically varying the set-up with other more powerful processor, more main memory capacity as well as faster interconnects. Hopefully, that this project will give benefits to all students and lectures to do the right research direction and fortunately this will provide future research work with ample room for problem testing and measurement of parallel processing
format	Thesis
qualification_level	Bachelor degree
author	Che Ibrahim, Mohd Erman Safawie
author_facet	Che Ibrahim, Mohd Erman Safawie
author_sort	Che Ibrahim, Mohd Erman Safawie
title	Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
title_short	Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
title_full	Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
title_fullStr	Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
title_full_unstemmed	Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim
title_sort	parallel genetic algorithms for shortest path routing in high- performance computing / mohd erman safawie che ibrahim
granting_institution	Universiti Teknologi MARA Terengganu
granting_department	Faculty of Computer & Mathematical Sciences
publishDate	2012
url	https://ir.uitm.edu.my/id/eprint/35330/1/35330.pdf
_version_	1783734298635927552

Parallel genetic algorithms for shortest path routing in high- performance computing / Mohd Erman Safawie Che Ibrahim

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