2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 13 , Issue 2 , PP: 129-140, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Zainab A. Abdulazeez 1 * , Nihad Abduljalil 2 , Ahmed B. M. Fanfakh 3 , Ali Kadhum M. Al-Qurabat 4 , Esraa H. Alwan 5
Doi: https://doi.org/10.54216/JISIoT.130210
Dynamic voltage and frequency scaling (DVFS) is a tool used primarily to decrease computer processor energy consumption by lowering its operational frequency. Their only downside is that they distract from the efficiency of parallel applications while operating on parallel platforms. In a heterogeneous cluster architecture, however, a genetic algorithm is being implemented and applied to model the best trade-off between energy-saving and parallel application performance degradation. The proposed algorithm selects the best frequency vector in order to accomplish these objectives by providing the same compromise. So, the objective function of the genetic algorithm at the same time gives limited energy consumption and minimum decreases in performance. The SimGrid simulator will be used for all experiments. The suggested algorithm saves the average energy by (20 %) and the application performance degrades to the limit (0.15 %).
Genetic algorithm , heterogeneous cluster , frequency scaling , energy consumption
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