THE ADVANTAGE OF GENETIC ALGORITHM IN ENERGY-EFFICIENT SCHEDULING FOR HETEROGENEOUS CLOUD COMPUTING - Zhou, Hang; Kausar, Samina; Dong, Ningning (International Journal of Research -GRANTHAALAYAH, 2016)
Nowadays Energy Consumption has been a heavy burden on the enterprise cloud computing infrastructure. This paper focuses on the hardware factors in energy consumption. Inspired by DVFS, it proposes a new energy-efficient (EE) model. This paper formulates the scheduling problem and genetic algorithm is applied to obtain higher efficiency value. Simulations are implemented to verify the advantage of genetic algorithm. In addition, the robustness of our strategy is validated by modifying the relevant parameters of the experiment.