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Dynamic scheduling of tasks for multi-core real-time systems based on optimum energy and throughput

One of the critical design issues in real-time systems is energy consumption, especially in battery-operated systems. Generally higher processor voltage generates higher throughput of the system while decreasing voltage can perform energy minimisation. Instead of lowering processor voltage, this paper presents an optimum energy efficient real-time scheduling to adjust voltage dynamically to achieve optimum throughput. Earlier research works have considered random new tasks, which have been divided into jobs using pfair scheduling to fit into idle times of different cores of the system. In this paper we consider each job has different power levels and execution time at each power level can be found using normalised execution time. Based on the power levels and their corresponding execution time, we find different combinations of energy signature of the system and derive the optimum state of the system using a weighted average of the energy of the system and corresponding throughput. We verify the proposed model using generated task sets and the results show that the model performs excellently in all the cases and significantly reduced the total energy consumption of the system with respect to some popular and relatively new scheduling schemes.