Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment

Cloud computing is a platform in which it provides services, information and software over the Internet. The essential role of cloud computing is enabling sharing of resources on-demand over the network (e.g. servers, applications, storage, services and database) to the end-users that are distribute...

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主要作者:	Mohammed, Faten Ameen Saif
格式:	Thesis
語言:	English
出版:	2019
主題:	Cloud computing - Case studies Hybrid computers - Programming
在線閱讀:	http://psasir.upm.edu.my/id/eprint/82950/1/FSKTM%202019%2032%20IR.pdf
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record_format	uketd_dc
spelling	my-upm-ir.829502020-07-24T00:27:38Z Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment 2019-01 Mohammed, Faten Ameen Saif Cloud computing is a platform in which it provides services, information and software over the Internet. The essential role of cloud computing is enabling sharing of resources on-demand over the network (e.g. servers, applications, storage, services and database) to the end-users that are distributed geographically. Task scheduling is a significant function in the cloud computing that plays a vital role to raise the rate of efficiency and the performance of the system. Task scheduling is considered as an NP-complete problem. However, the heterogeneity of resources in the cloud environment put the scheduling in a critical issue. Furthermore, heuristic algorithms do not have the required level of efficiency to optimize the scheduling and the performance in this environment. Thus, this study focuses on optimizing the hybrid meta-heuristic (genetic algorithm along with DE algorithm that minimizes the completion time and enhances the performance of the task scheduling. The results will be compared with a three heuristic algorithms. The performance evaluation in this work is a statically analysis that used in an experimental comparison. The expected result of this study is optimizing the overall of completion time and enhancing resource efficiency. Cloud computing - Case studies Hybrid computers - Programming 2019-01 Thesis http://psasir.upm.edu.my/id/eprint/82950/ http://psasir.upm.edu.my/id/eprint/82950/1/FSKTM%202019%2032%20IR.pdf text en public masters Universiti Putra Malaysia Cloud computing - Case studies Hybrid computers - Programming Derahman, Mohd. Noor
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Derahman, Mohd. Noor
topic	Cloud computing - Case studies Hybrid computers - Programming
spellingShingle	Cloud computing - Case studies Hybrid computers - Programming Mohammed, Faten Ameen Saif Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
description	Cloud computing is a platform in which it provides services, information and software over the Internet. The essential role of cloud computing is enabling sharing of resources on-demand over the network (e.g. servers, applications, storage, services and database) to the end-users that are distributed geographically. Task scheduling is a significant function in the cloud computing that plays a vital role to raise the rate of efficiency and the performance of the system. Task scheduling is considered as an NP-complete problem. However, the heterogeneity of resources in the cloud environment put the scheduling in a critical issue. Furthermore, heuristic algorithms do not have the required level of efficiency to optimize the scheduling and the performance in this environment. Thus, this study focuses on optimizing the hybrid meta-heuristic (genetic algorithm along with DE algorithm that minimizes the completion time and enhances the performance of the task scheduling. The results will be compared with a three heuristic algorithms. The performance evaluation in this work is a statically analysis that used in an experimental comparison. The expected result of this study is optimizing the overall of completion time and enhancing resource efficiency.
format	Thesis
qualification_level	Master's degree
author	Mohammed, Faten Ameen Saif
author_facet	Mohammed, Faten Ameen Saif
author_sort	Mohammed, Faten Ameen Saif
title	Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
title_short	Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
title_full	Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
title_fullStr	Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
title_full_unstemmed	Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
title_sort	performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment
granting_institution	Universiti Putra Malaysia
publishDate	2019
url	http://psasir.upm.edu.my/id/eprint/82950/1/FSKTM%202019%2032%20IR.pdf
_version_	1747813334733815808

Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment

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