Abstract
In this paper, by taking both memory-access and computation time cost into consideration, a two-phase execution, i.e. memory-access phase first to fetch the instructions and required data, and then computation, is proposed to model mixed criticality tasks. Based on the proposed task model, a fixed-priority based scheduling algorithm is developed to schedule the mixed-criticality tasks. We first establish the theoretical foundations upon which to determine whether if a mixed-criticality task set is schedulable under given memory-access and computation priorities; and then based on these theoretical conclusions, we further present how to apply the well-known Audsley’s algorithm to find the optimal priority assignment for both memory-access and computation phases. Extensive experiments have been conducted and the experimental results validate the effectiveness of our proposed approach.
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Li, Z., Wang, L. (2016). Memory-Aware Scheduling for Mixed-Criticality Systems. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9787. Springer, Cham. https://doi.org/10.1007/978-3-319-42108-7_11
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DOI: https://doi.org/10.1007/978-3-319-42108-7_11
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