Scheduling divisible jobs to optimize the computation and energy costs
The important challenge in cloud computing environment is to design a scheduling strategy to handle jobs, and to process them in a heterogeneous environment with shared data centers. In this paper, we attempt to investigate a new analytical framework model that enables an existing private cloud data...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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International Journal of Engineering and Science Invention
2015
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| Online Access: | http://psasir.upm.edu.my/id/eprint/46221/ http://psasir.upm.edu.my/id/eprint/46221/1/Scheduling%20divisible%20jobs%20to%20optimize%20the%20computation%20and%20energy%20costs.pdf |
| _version_ | 1848850618882457600 |
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| author | Abdullah, Monir Othman, Mohamed |
| author_facet | Abdullah, Monir Othman, Mohamed |
| author_sort | Abdullah, Monir |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The important challenge in cloud computing environment is to design a scheduling strategy to handle jobs, and to process them in a heterogeneous environment with shared data centers. In this paper, we attempt to investigate a new analytical framework model that enables an existing private cloud data-center for scheduling jobs and minimizing the overall computation and energy cost together. Our model is based on Divisible Load Theory (DLT) model to derive closed-form solution for the load fractions to be assigned to each machines considering computation and energy cost. Our analysis also attempts to schedule the jobs such a way that cloud provider can gain maximum benefit for his service and Quality of Service (QoS) requirement user’s job. Finally, we quantify the performance of the strategies via rigorous simulation studies. |
| first_indexed | 2025-11-15T10:09:10Z |
| format | Article |
| id | upm-46221 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:09:10Z |
| publishDate | 2015 |
| publisher | International Journal of Engineering and Science Invention |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-462212018-03-30T13:15:51Z http://psasir.upm.edu.my/id/eprint/46221/ Scheduling divisible jobs to optimize the computation and energy costs Abdullah, Monir Othman, Mohamed The important challenge in cloud computing environment is to design a scheduling strategy to handle jobs, and to process them in a heterogeneous environment with shared data centers. In this paper, we attempt to investigate a new analytical framework model that enables an existing private cloud data-center for scheduling jobs and minimizing the overall computation and energy cost together. Our model is based on Divisible Load Theory (DLT) model to derive closed-form solution for the load fractions to be assigned to each machines considering computation and energy cost. Our analysis also attempts to schedule the jobs such a way that cloud provider can gain maximum benefit for his service and Quality of Service (QoS) requirement user’s job. Finally, we quantify the performance of the strategies via rigorous simulation studies. International Journal of Engineering and Science Invention 2015-02 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/46221/1/Scheduling%20divisible%20jobs%20to%20optimize%20the%20computation%20and%20energy%20costs.pdf Abdullah, Monir and Othman, Mohamed (2015) Scheduling divisible jobs to optimize the computation and energy costs. International Journal of Engineering and Science Invention, 4 (2). pp. 27-33. ISSN 2319–6726; ESSN: 2319–6734 http://www.ijesi.org |
| spellingShingle | Abdullah, Monir Othman, Mohamed Scheduling divisible jobs to optimize the computation and energy costs |
| title | Scheduling divisible jobs to optimize the computation and energy costs |
| title_full | Scheduling divisible jobs to optimize the computation and energy costs |
| title_fullStr | Scheduling divisible jobs to optimize the computation and energy costs |
| title_full_unstemmed | Scheduling divisible jobs to optimize the computation and energy costs |
| title_short | Scheduling divisible jobs to optimize the computation and energy costs |
| title_sort | scheduling divisible jobs to optimize the computation and energy costs |
| url | http://psasir.upm.edu.my/id/eprint/46221/ http://psasir.upm.edu.my/id/eprint/46221/ http://psasir.upm.edu.my/id/eprint/46221/1/Scheduling%20divisible%20jobs%20to%20optimize%20the%20computation%20and%20energy%20costs.pdf |