While the dynamic voltage scaling (DVS) techniques are efficient in reducing the dynamic energy consumption for the processor, varying voltage alone becomes less effective for the overall power reduction as the leakage power is growing rapidly, i.e., five times per technical generation as predicted. On the other hand, Quality of Service (QoS) is also a primary concern in the development of today’s pervasive computing systems. In this paper, we study the problem of minimizing the overall energy consumption for soft real-time systems while ensuring the QoS-guarantee. In our research, the QoS requirements are deterministically quantified with the (m,k)-constraints, which require that at least m out of any k consecutive jobs of a task meet their deadlines. Two approaches are proposed in this paper. One statically determines the mandatory jobs that have to meet their deadlines in order to satisfy the (m,k)-constraints, and the other one does so dynamically. Moreover, we present efficient scheduling techniques to reduce the overall energy by procrastinating the execution of mandatory jobs and thus to merge the idle intervals. The simulation results demonstrate that our proposed techniques significantly outperformed previous research in both overall and idle energy reduction while providing the (m,k)-guarantee.

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