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- W2019421013 abstract "The cost of electricity for datacenters is a substantial operational cost that can and should be managed, not only for saving energy, but also due to the ecologic commitment inherent to power consumption. This work proposes, formalizes and numerically evaluates LEAS, a low-energy scheduling model, for clearing scheduling markets, based on the maximization of welfare, subject to utility-level dependant energy costs. We promote energy-efficient policies in management of datacenters, to enhance the efficiency of modernized datacenters. We focus specifically on linear power models, and the implications of the inherent fixed costs related to energy consumption of modern datacenters. We rigorously test the model by running multiple simulation scenarios derived from real workload traces, and evaluate the results using common statistical methods. We conclude with positive results and implications for long-term sustainable management of modern datacenters." @default.
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- W2019421013 date "2011-06-14" @default.
- W2019421013 modified "2023-09-27" @default.
- W2019421013 title "Low-energy automated scheduling of computing resources" @default.
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- W2019421013 doi "https://doi.org/10.1145/1998561.1998566" @default.
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