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• W2125381034 abstract "We address power-aware scheduling of periodic tasks to reduce CPU energy consumption in hard real-time systems through dynamic voltage scaling. Our intertask voltage scheduling solution includes three components: 1) a static (offline) solution to compute the optimal speed, assuming worst-case workload for each arrival, 2) an online speed reduction mechanism to reclaim energy by adapting to the actual workload, and 3) an online, adaptive and speculative speed adjustment mechanism to anticipate early completions of future executions by using the average-case workload information. All these solutions still guarantee that all deadlines are met. Our simulation results show that our reclaiming algorithm alone outperforms other recently proposed intertask voltage scheduling schemes. Our speculative techniques are shown to provide additional gains, approaching the theoretical lower-bound by a margin of 10 percent." @default.
• W2125381034 created "2016-06-24" @default.
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• W2125381034 date "2004-05-01" @default.
• W2125381034 modified "2023-10-01" @default.
• W2125381034 title "Power-aware scheduling for periodic real-time tasks" @default.
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• W2125381034 doi "https://doi.org/10.1109/tc.2004.1275298" @default.
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