Abstract
Energy consumption and elevating the chip temperature become a serious challenge in designing embedded systems mainly due to transistor scaling and integration of more components into a single chip. The temperature of the chip has significant effects on leakage current, energy consumption and reliability of the chip; hence, discovering a mechanism that reduces both energy consumption and temperature of the chip is of utmost significance. An effective task scheduling in a real-time multiprocessor system-on-chip system has a direct impact on energy consumption and temperature of the chip. Several task scheduling and task assignment techniques have been proposed to achieve this goal. Most of those works consider only utilization of processors to distribute tasks among processors in order to reduce energy consumption. Meanwhile, those works try to reduce temperature in the step of task scheduling, separately in each processor. This paper proposes a fuzzy-based technique to distribute real-time tasks among processors in order to reduce both temperature and energy consumption simultaneously. Simulation results show that our proposed technique is more efficient in terms of reducing the energy consumption compared to a well-known state-of-the-art method (up to 9%) while offering a more balanced and moderate temperatures for processors and hindering hot spot.
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Ekhtiyari, Z., Moghaddas, V. & Beitollahi, H. A temperature-aware and energy-efficient fuzzy technique to schedule tasks in heterogeneous MPSoC systems. J Supercomput 75, 5398–5419 (2019). https://doi.org/10.1007/s11227-019-02807-8
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DOI: https://doi.org/10.1007/s11227-019-02807-8