Adaptive runtime shaping for mixed-criticality systems

This paper investigates runtime shaping for mixed-criticality systems to increase the system QoS. Unlike the previous work in the literature that enforces an offline workload bound, an adaptively shaping approach is proposed where the incoming workload of the low-critical tasks is regulated by the actual demand of the high-critical tasks. This actual demand is adaptively updated using the historical arrival information of the high-critical tasks and thus can maximize the runtime QoS of low-critical tasks. To reduce the online overheads of computing the workload demand, a lightweight scheme with the complexity of O(n log(m)) is developed. Experiments are also provided to demonstrate the effectiveness and efficiency of our approach.