Replica Creation Algorithm for Data Grids

Data grid system is a data management infrastructure that facilitates reliable access and sharing of large amount of data, storage resources, and data transfer services that can be scaled across distributed locations. This thesis presents a new replication algorithm that improves data access perform...

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Main Author:	Madi, Mohammed Kamel
Format:	Thesis
Language:	eng eng
Published:	2012
Subjects:	QA71-90 Instruments and machines
Online Access:	https://etd.uum.edu.my/3352/1/MOHAMMED_KAMEL_MADI.pdf https://etd.uum.edu.my/3352/3/MOHAMMED_KAMEL_MADI.pdf
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id	my-uum-etd.3352
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Hassan, Suhaidi Yusof, Yuhanis
topic	QA71-90 Instruments and machines
spellingShingle	QA71-90 Instruments and machines Madi, Mohammed Kamel Replica Creation Algorithm for Data Grids
description	Data grid system is a data management infrastructure that facilitates reliable access and sharing of large amount of data, storage resources, and data transfer services that can be scaled across distributed locations. This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. The new Data Replica Creation Algorithm (DRCM) improves performance of data grid systems by reducing job execution time and making the best use of data grid resources (network bandwidth and storage space). Current algorithms focus on number of accesses in deciding which file to replicate and where to place them, which ignores resources’ capabilities. DRCM differs by considering both user and resource perspectives; strategically placing replicas at locations that provide the lowest transfer cost. The proposed algorithm uses three strategies: Replica Creation and Deletion Strategy (RCDS), Replica Placement Strategy (RPS), and Replica Replacement Strategy (RRS). DRCM was evaluated using network simulation (OptorSim) based on selected performance metrics (mean job execution time, efficient network usage, average storage usage, and computing element usage), scenarios, and topologies. Results revealed better job execution time with lower resource consumption than existing approaches. This research contributes replication strategies embodied in one algorithm that enhances data grid performance, capable of making a decision on creating or deleting more than one file during same decision. Furthermore, dependency-level-between-files criterion was utilized and integrated with the exponential growth/decay model to give an accurate file evaluation.
format	Thesis
qualification_name	Ph.D.
qualification_level	Doctorate
author	Madi, Mohammed Kamel
author_facet	Madi, Mohammed Kamel
author_sort	Madi, Mohammed Kamel
title	Replica Creation Algorithm for Data Grids
title_short	Replica Creation Algorithm for Data Grids
title_full	Replica Creation Algorithm for Data Grids
title_fullStr	Replica Creation Algorithm for Data Grids
title_full_unstemmed	Replica Creation Algorithm for Data Grids
title_sort	replica creation algorithm for data grids
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2012
url	https://etd.uum.edu.my/3352/1/MOHAMMED_KAMEL_MADI.pdf https://etd.uum.edu.my/3352/3/MOHAMMED_KAMEL_MADI.pdf
_version_	1776103616305692672
spelling	my-uum-etd.33522023-03-01T01:27:46Z Replica Creation Algorithm for Data Grids 2012 Madi, Mohammed Kamel Hassan, Suhaidi Yusof, Yuhanis Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts & Sciences QA71-90 Instruments and machines Data grid system is a data management infrastructure that facilitates reliable access and sharing of large amount of data, storage resources, and data transfer services that can be scaled across distributed locations. This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. The new Data Replica Creation Algorithm (DRCM) improves performance of data grid systems by reducing job execution time and making the best use of data grid resources (network bandwidth and storage space). Current algorithms focus on number of accesses in deciding which file to replicate and where to place them, which ignores resources’ capabilities. DRCM differs by considering both user and resource perspectives; strategically placing replicas at locations that provide the lowest transfer cost. The proposed algorithm uses three strategies: Replica Creation and Deletion Strategy (RCDS), Replica Placement Strategy (RPS), and Replica Replacement Strategy (RRS). DRCM was evaluated using network simulation (OptorSim) based on selected performance metrics (mean job execution time, efficient network usage, average storage usage, and computing element usage), scenarios, and topologies. Results revealed better job execution time with lower resource consumption than existing approaches. This research contributes replication strategies embodied in one algorithm that enhances data grid performance, capable of making a decision on creating or deleting more than one file during same decision. Furthermore, dependency-level-between-files criterion was utilized and integrated with the exponential growth/decay model to give an accurate file evaluation. 2012 Thesis https://etd.uum.edu.my/3352/ https://etd.uum.edu.my/3352/1/MOHAMMED_KAMEL_MADI.pdf text eng public https://etd.uum.edu.my/3352/3/MOHAMMED_KAMEL_MADI.pdf text eng public http://sierra.uum.edu.my/record=b1239722~S1 Ph.D. doctoral Universiti Utara Malaysia J.P.M.G.A.Gravvanis, H.R.Arabina, D.A.Power, "Grid Technology and Applications: Recent Developments," New York: Nova Science Publishers, Inc., 2009. I.Foster and C.Kesselman, "The Grid: Blueprint for a New Computing Infrastructure," San Francisco: Morgan Kaufmann Publishers, vol. 24, p. 8, 1999. S.Venugopal, R.Buyya, and L.Winton, "A Grid service broker for scheduling e Science applications on global data Grids," Concurrency and Computation: Practice and Experience, vol. 18, pp. 685-699, 2006. 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