Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.
Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2016-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4934704?pdf=render |
| _version_ | 1830429813460959232 |
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| author | Shafi'i Muhammad Abdulhamid Muhammad Shafie Abd Latiff Gaddafi Abdul-Salaam Syed Hamid Hussain Madni |
| author_facet | Shafi'i Muhammad Abdulhamid Muhammad Shafie Abd Latiff Gaddafi Abdul-Salaam Syed Hamid Hussain Madni |
| author_sort | Shafi'i Muhammad Abdulhamid |
| collection | DOAJ |
| description | Cloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques. |
| first_indexed | 2024-12-21T01:38:33Z |
| format | Article |
| id | doaj.art-78067c7634564e2aa6dd7a173447ec6b |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-21T01:38:33Z |
| publishDate | 2016-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-78067c7634564e2aa6dd7a173447ec6b2022-12-21T19:20:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01117e015810210.1371/journal.pone.0158102Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm.Shafi'i Muhammad AbdulhamidMuhammad Shafie Abd LatiffGaddafi Abdul-SalaamSyed Hamid Hussain MadniCloud computing system is a huge cluster of interconnected servers residing in a datacenter and dynamically provisioned to clients on-demand via a front-end interface. Scientific applications scheduling in the cloud computing environment is identified as NP-hard problem due to the dynamic nature of heterogeneous resources. Recently, a number of metaheuristics optimization schemes have been applied to address the challenges of applications scheduling in the cloud system, without much emphasis on the issue of secure global scheduling. In this paper, scientific applications scheduling techniques using the Global League Championship Algorithm (GBLCA) optimization technique is first presented for global task scheduling in the cloud environment. The experiment is carried out using CloudSim simulator. The experimental results show that, the proposed GBLCA technique produced remarkable performance improvement rate on the makespan that ranges between 14.44% to 46.41%. It also shows significant reduction in the time taken to securely schedule applications as parametrically measured in terms of the response time. In view of the experimental results, the proposed technique provides better-quality scheduling solution that is suitable for scientific applications task execution in the Cloud Computing environment than the MinMin, MaxMin, Genetic Algorithm (GA) and Ant Colony Optimization (ACO) scheduling techniques.http://europepmc.org/articles/PMC4934704?pdf=render |
| spellingShingle | Shafi'i Muhammad Abdulhamid Muhammad Shafie Abd Latiff Gaddafi Abdul-Salaam Syed Hamid Hussain Madni Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm. PLoS ONE |
| title | Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm. |
| title_full | Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm. |
| title_fullStr | Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm. |
| title_full_unstemmed | Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm. |
| title_short | Secure Scientific Applications Scheduling Technique for Cloud Computing Environment Using Global League Championship Algorithm. |
| title_sort | secure scientific applications scheduling technique for cloud computing environment using global league championship algorithm |
| url | http://europepmc.org/articles/PMC4934704?pdf=render |
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