Energy minimization for real-time systems with (m,k)-guarantee

Energy consumption and quality of service (QoS) are two primary concerns in the development of today's pervasive computing systems. While most of the current research in energy-aware real-time scheduling has been focused on hard real-time systems, a large number of practical applications and systems exhibit more soft real-time nature. In this paper, we study the problem of minimizing energy for soft real-time systems while providing a QoS guarantee. 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. In this paper, we propose a hybrid approach to achieve the dual goals of QoS guarantee and energy minimization. We first present the necessary and sufficient schedulability conditions for the static mandatory/optional workload partitioning. Then, we propose to dynamically vary the statically defined mandatory/optional partitions to accommodate dynamic run-time variations while minimizing the energy consumption. The experimental results demonstrate that our proposed techniques outperform previous work significantly in terms of both the energy savings and achieved QoS.