Reliability-aware scheduling for (m,k)-firm real-time embedded systems under hard energy budget constraint

For real-time embedded systems, feasibility, Quality of Service (QoS), reliability, and energy constraint are among the primary design concerns. In this research, we proposed a reliability-aware scheduling scheme for real-time embedded systems with $(m,k)$-firm deadlines under hard energy budget constraint. The $(m,k)$-firm systems require that at least $m$ out of any $k$ consecutive jobs of a real-time task meet their deadlines. To achieve the dual goals of maximizing the feasibility and QoS for such kind of systems while satisfying the reliability requirement under given energy budget constraint, we propose to reserve recovery space for real-time jobs in an adaptive way based on the mandatory/optional job partitioning strategy. The evaluation results demonstrate that the proposed techniques significantly outperform the previous research in maximizing the feasibility and QoS for $(m,k)$-firm real-time embedded systems while preserving the system reliability under hard energy budget constraint. Moreover, the proposed work has also addressed some insufficiency in Niu (2020) in terms of preserving the system reliability.