Modified MUF and EDF algorithms for overloaded soft real time systems
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Dynamic task set partitioning based on balancing memory requirements to reduce power consumption
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Energy reduction techniques for systems with non-DVS components
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Energy minimization for real-time systems with non-convex and discrete operation modes
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Platform synthesis and partitioning of real-time tasks for energy efficiency
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An experimental evaluation of real-time DVFS scheduling algorithms
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Energy-efficient tasks scheduling algorithm for real-time multiprocessor embedded systems
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Efficient task scheduling for hard real-time tasks in asymmetric multicore processors
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Multiple processing elements are often adopted in the current designs of embedded systems. Such configurations impose challenges on hardware/software co-designs with energy-efficient considerations. This paper targets energy-efficient real-time task scheduling of such popular configurations, in which systems are equipped with a DVS processor and a non-DVS processing element (PE). We consider task scheduling under different power consumption models of the non-DVS PE. When the power consumption of the non-DVS PE is independent on the assigned workload, a fully polynomial-time approximation scheme is developed for energy-efficient scheduling. When the energy consumption of the non-DVS PE depends on the assigned workload, a 0.5-approximation algorithm is developed to maximize the energy saving, compared to the execution of tasks on a DVS processor. Extensive simulations were performed to evaluate the capability of our proposed algorithms. The results show that our algorithms are very effective in energy-efficiency.