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- W2597697922 abstract "Due to increasing energy requirements and associated environmental impacts, nowadays most embedded systems suffer from resource constraints as they are designed for applications that run in real-time. Many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of dynamic voltage scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a new hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and neural feedback planning (NFP) with the energy priority earlier deadline first (PEDF) algorithm. The preliminary experiments to compare the reconfigurable resulting from conventional methods are presented. The results are then discussed." @default.
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- W2597697922 date "2017-01-12" @default.
- W2597697922 modified "2023-09-23" @default.
- W2597697922 title "Optimal Solutions for Real-Time Scheduling of Reconfigurable Embedded Systems Based on Neural Networks with Minimization of Power Consumption" @default.
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