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• W3036320021 abstract "Heterogeneous green scheduling in virtual cloud is an urgent need of human sustainable developments. However, on the one hand, there is still considerable space beyond reach of the hardware energy regulation mode; on the other hand, as the core of green software methods, meta-heuristics algorithms are still underperforming in heterogeneous scheduling, although with many achievements in homogeneous scheduling. In this paper, an efficient new meta-heuristics algorithm is presented (i.e., GHSA_di), including the co-evolutionary dynamics equation emphasizing on and taking advantage of the hardware energy-regulation principles. The experimental results show that compared with the other three meta-heuristic scheduling algorithms, GHSA_di algorithm has obvious advantages in overall performance, energy saving and scalability, for both data intensive and computing intensive instances." @default.
• W3036320021 created "2020-06-25" @default.
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• W3036320021 date "2020-01-01" @default.
• W3036320021 modified "2023-10-14" @default.
• W3036320021 title "An Algorithm Incarnating Deep Integration of Hardware-Software Energy Regulation Principles for Heterogeneous Green Scheduling" @default.
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• W3036320021 doi "https://doi.org/10.1109/access.2020.3003304" @default.
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