Abstract
Many real-time applications with different criticalities are integrated into a single mixed-criticality (MC) real-time system. Previous studies on MC systems assume that all tasks are executed in their worst case execution time and ignore the energy consumption in the high-criticality mode. In this paper, we focus on the actual execution time of tasks and consider the energy consumption in both the low-criticality mode and the high-criticality mode. First, we present a novel algorithm called EAU, which applies the actual execution time to re-compute the utilization of the task when a job is completed early or is released. In addition, it can apply the slack time generated from the early completion jobs and the jobs for which the processor speed is lower than the maximum processor speed in the high-criticality mode. Secondly, we analyze the scheduling feasibility of EAU. Finally, experiments are conducted to evaluate the performance of the proposed algorithm. The experimental results show that EAU can save up to 46.84% of energy compared with existing algorithms.
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