An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong

The use of Grid and Cloud Computing for resource sharing has received tremendous attention in recent years. The merging of virtualization, utility computing and distributed computing with Service Oriented Architecture (SOA) has provided greater flexibility and ushered in a new paradigm of on-demand...

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Main Author: Ang, Tan Fong
Format: Thesis
Published: 2011
Subjects:
Online Access:http://pendeta.um.edu.my/client/default/search/results?qu=An+adaptive+QOS+scheduling+algorithm+in+service+oriented+grid+and+cloud+environment&te=
http://studentsrepo.um.edu.my/3580/4/Title_page%2C_abstract%2C_content.pdf
http://studentsrepo.um.edu.my/3580/5/CHAPTER_1_%2D_6.pdf
http://studentsrepo.um.edu.my/3580/6/References_%26_appendices.pdf
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author Ang, Tan Fong
author_facet Ang, Tan Fong
author_sort Ang, Tan Fong
building UM Research Repository
collection Online Access
description The use of Grid and Cloud Computing for resource sharing has received tremendous attention in recent years. The merging of virtualization, utility computing and distributed computing with Service Oriented Architecture (SOA) has provided greater flexibility and ushered in a new paradigm of on-demand services. However, job scheduling remains a formidable challenge due to the dynamic and heterogeneous nature of Grid and Cloud Computing. Furthermore, the increasing and diverse end users requests raise new and greater urgencies to resolve the provisioning of Quality of Service (QoS). This thesis proposes a Hybrid Scheduling Algorithm (HSA) with automatic deployment mechanism that maximizes resources utilization and minimizes total makespan. Subsequently, an Adaptive Scheduling Algorithm (ASA) that uses benchmarking is proposed to enhance the HSA. ASA is able to optimize the job scheduling performance over other approaches. Finally, Adaptive QoS Scheduling Algorithm (AQoSSA), an enhancement of ASA, is presented to meet the varied users QoS requirements. AQoSSA is able to maximize reliability and profit while guaranteeing the users’ QoS requirements. An experimental testbed is developed to evaluate the performances of all the proposed algorithms. The makespan results showed that the HSA and ASA outperformed the conventional MIN-MIN and MAX-MIN by between 1% - 10% and 5% - 17% respectively. Whereas, AQoSSA outperformed MIN-MIN QoS and MAX-MIN QoS by between 3% - 6% and 10% - 47% in terms of reliability and profit respectively while guaranteeing the users’ QoS requirements.
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format Thesis
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institution University Malaya
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last_indexed 2025-11-14T13:26:41Z
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spelling um-35802013-09-18T04:46:55Z An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong Ang, Tan Fong QA Mathematics QA76 Computer software The use of Grid and Cloud Computing for resource sharing has received tremendous attention in recent years. The merging of virtualization, utility computing and distributed computing with Service Oriented Architecture (SOA) has provided greater flexibility and ushered in a new paradigm of on-demand services. However, job scheduling remains a formidable challenge due to the dynamic and heterogeneous nature of Grid and Cloud Computing. Furthermore, the increasing and diverse end users requests raise new and greater urgencies to resolve the provisioning of Quality of Service (QoS). This thesis proposes a Hybrid Scheduling Algorithm (HSA) with automatic deployment mechanism that maximizes resources utilization and minimizes total makespan. Subsequently, an Adaptive Scheduling Algorithm (ASA) that uses benchmarking is proposed to enhance the HSA. ASA is able to optimize the job scheduling performance over other approaches. Finally, Adaptive QoS Scheduling Algorithm (AQoSSA), an enhancement of ASA, is presented to meet the varied users QoS requirements. AQoSSA is able to maximize reliability and profit while guaranteeing the users’ QoS requirements. An experimental testbed is developed to evaluate the performances of all the proposed algorithms. The makespan results showed that the HSA and ASA outperformed the conventional MIN-MIN and MAX-MIN by between 1% - 10% and 5% - 17% respectively. Whereas, AQoSSA outperformed MIN-MIN QoS and MAX-MIN QoS by between 3% - 6% and 10% - 47% in terms of reliability and profit respectively while guaranteeing the users’ QoS requirements. 2011 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/3580/4/Title_page%2C_abstract%2C_content.pdf application/pdf http://studentsrepo.um.edu.my/3580/5/CHAPTER_1_%2D_6.pdf application/pdf http://studentsrepo.um.edu.my/3580/6/References_%26_appendices.pdf http://pendeta.um.edu.my/client/default/search/results?qu=An+adaptive+QOS+scheduling+algorithm+in+service+oriented+grid+and+cloud+environment&te= Ang, Tan Fong (2011) An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/3580/
spellingShingle QA Mathematics
QA76 Computer software
Ang, Tan Fong
An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong
title An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong
title_full An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong
title_fullStr An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong
title_full_unstemmed An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong
title_short An adaptive QOS scheduling algorithm in service oriented grid and cloud environment / Ang Tan Fong
title_sort adaptive qos scheduling algorithm in service oriented grid and cloud environment / ang tan fong
topic QA Mathematics
QA76 Computer software
url http://pendeta.um.edu.my/client/default/search/results?qu=An+adaptive+QOS+scheduling+algorithm+in+service+oriented+grid+and+cloud+environment&te=
http://pendeta.um.edu.my/client/default/search/results?qu=An+adaptive+QOS+scheduling+algorithm+in+service+oriented+grid+and+cloud+environment&te=
http://studentsrepo.um.edu.my/3580/4/Title_page%2C_abstract%2C_content.pdf
http://studentsrepo.um.edu.my/3580/5/CHAPTER_1_%2D_6.pdf
http://studentsrepo.um.edu.my/3580/6/References_%26_appendices.pdf