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• W2019292693 abstract "Many wireless embedded systems must deal with increasingly complex and time-varying workloads. Moreover, real-time constraints must be satisfied. Most of the existing energy management studies for such systems have focused on relatively simple models that assume deterministic workloads and consider a limited range of energy management techniques, including Dynamic Voltage Scaling (DVS). Our paper addresses these deficiencies by proposing a general purpose probabilistic workload model for computation and communication. To account for the importance of radio energy consumption, we also analyse Dynamic Modulation Scaling (DMS), an often overlooked method for energy management. We define several energy control algorithms, including an optimal combined DVS-DMS approach, and evaluate these algorithms under a wide range of workload values and hardware settings. Our results illustrate the benefits of various power control algorithms." @default.
• W2019292693 created "2016-06-24" @default.
• W2019292693 creator A5010846802 @default.
• W2019292693 creator A5031348513 @default.
• W2019292693 creator A5057010979 @default.
• W2019292693 date "2014-11-01" @default.
• W2019292693 modified "2023-09-24" @default.
• W2019292693 title "Energy management of embedded wireless systems through voltage and modulation scaling under probabilistic workloads" @default.
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• W2019292693 doi "https://doi.org/10.1109/igcc.2014.7039168" @default.
• W2019292693 hasPublicationYear "2014" @default.
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