Multi-objective Optimization of Grid Computing for Performance, Energy and Cost
In this paper, new multi-objective optimization algorithm is proposed. It optimizes the execution time, the energy consumption and the cost of booked nodes in the grid architecture at the same time. The proposed algorithm selects the best frequencies depends on a new optimization function that optim...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sulaimani Polytechnic University
2017-08-01
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| Series: | Kurdistan Journal of Applied Research |
| Subjects: | |
| Online Access: | http://kjar.spu.edu.iq/index.php/kjar/article/view/100 |
| _version_ | 1828882515251691520 |
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| author | Ahmed Badri Muslim Fanfakhri Ali Yakoob Yousif Esraa Alwan |
| author_facet | Ahmed Badri Muslim Fanfakhri Ali Yakoob Yousif Esraa Alwan |
| author_sort | Ahmed Badri Muslim Fanfakhri |
| collection | DOAJ |
| description | In this paper, new multi-objective optimization algorithm is proposed. It optimizes the execution time, the energy consumption and the cost of booked nodes in the grid architecture at the same time. The proposed algorithm selects the best frequencies depends on a new optimization function that optimized these three objectives, while giving equivalent trade-off for each one. Dynamic voltage and frequency scaling (DVFS) is used to reduce the energy consumption of the message passing parallel iterative method executed over grid. DVFS is also reduced the computing power of each processor executing the parallel applications. Therefore, the performance of these applications is decreased and so on the payed cost for the booking nodes is increased. However, the proposed multi-objective algorithm gives the minimum energy consumption and minimum cost with maximum performance at the same time. The proposed algorithm is evaluated on the SimGrid/SMPI simulator while running the parallel iterative Jacobi method. The experiments show that it reduces on average the energy consumption by up to 19.7 %, while limiting the performance and cost degradations to 3.2 % and 5.2 % respectively. |
| first_indexed | 2024-12-13T10:29:55Z |
| format | Article |
| id | doaj.art-26cc802d62a94f40a28aea8d1baafeef |
| institution | Directory Open Access Journal |
| issn | 2411-7684 2411-7706 |
| language | English |
| last_indexed | 2024-12-13T10:29:55Z |
| publishDate | 2017-08-01 |
| publisher | Sulaimani Polytechnic University |
| record_format | Article |
| series | Kurdistan Journal of Applied Research |
| spelling | doaj.art-26cc802d62a94f40a28aea8d1baafeef2022-12-21T23:50:52ZengSulaimani Polytechnic UniversityKurdistan Journal of Applied Research2411-76842411-77062017-08-0123747910.24017/science.2017.3.31100Multi-objective Optimization of Grid Computing for Performance, Energy and CostAhmed Badri Muslim Fanfakhri0Ali Yakoob Yousif1Esraa Alwan2Computer Dept, College of Science for Women University of Babylon, IraqComputer Dept, College of Science for Women University of Babylon, IraqComputer Dept, College of Science for Women University of Babylon, IraqIn this paper, new multi-objective optimization algorithm is proposed. It optimizes the execution time, the energy consumption and the cost of booked nodes in the grid architecture at the same time. The proposed algorithm selects the best frequencies depends on a new optimization function that optimized these three objectives, while giving equivalent trade-off for each one. Dynamic voltage and frequency scaling (DVFS) is used to reduce the energy consumption of the message passing parallel iterative method executed over grid. DVFS is also reduced the computing power of each processor executing the parallel applications. Therefore, the performance of these applications is decreased and so on the payed cost for the booking nodes is increased. However, the proposed multi-objective algorithm gives the minimum energy consumption and minimum cost with maximum performance at the same time. The proposed algorithm is evaluated on the SimGrid/SMPI simulator while running the parallel iterative Jacobi method. The experiments show that it reduces on average the energy consumption by up to 19.7 %, while limiting the performance and cost degradations to 3.2 % and 5.2 % respectively.http://kjar.spu.edu.iq/index.php/kjar/article/view/100Multi-objective optimization, Grid computing, Parallel message passing iterative applications and DVFS. |
| spellingShingle | Ahmed Badri Muslim Fanfakhri Ali Yakoob Yousif Esraa Alwan Multi-objective Optimization of Grid Computing for Performance, Energy and Cost Kurdistan Journal of Applied Research Multi-objective optimization, Grid computing, Parallel message passing iterative applications and DVFS. |
| title | Multi-objective Optimization of Grid Computing for Performance, Energy and Cost |
| title_full | Multi-objective Optimization of Grid Computing for Performance, Energy and Cost |
| title_fullStr | Multi-objective Optimization of Grid Computing for Performance, Energy and Cost |
| title_full_unstemmed | Multi-objective Optimization of Grid Computing for Performance, Energy and Cost |
| title_short | Multi-objective Optimization of Grid Computing for Performance, Energy and Cost |
| title_sort | multi objective optimization of grid computing for performance energy and cost |
| topic | Multi-objective optimization, Grid computing, Parallel message passing iterative applications and DVFS. |
| url | http://kjar.spu.edu.iq/index.php/kjar/article/view/100 |
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