A paper entitled “Decoupling Criticality and Importance in Mixed-Criticality Scheduling” has been accepted at the 6th International Workshop on Mixed Criticality Systems (WMC).The paper addresses the need for more expressive task models for mixed-criticality systems by presenting an extension to the well-known mode-based adaptive mixed-criticality model by Vestal. The proposed model allows a task’s criticality and its importance to be specified independently from each other. A task’s importance is the criterion that determines its presence in different system modes. Meanwhile, the task’s criticality (reflected in its Safety Integrity Level (SIL) and defining the rules for its software development process), prescribes the degree of conservativeness for the task’s estimated WCET during schedulability testing.
We indicate how such a task model can help resolve some of the perceived weaknesses of the Vestal model, in terms of how it is interpreted, and demonstrate how the existing scheduling tests for the classic variant’s of Vestal’s model can be mapped to the new task model essentially without changes.
We celebrate the acceptance of our paper “Mixed-criticality Scheduling with Dynamic Memory Bandwidth Regulation” at RTCSA. This paper is the next step in my research collaboration with CISTER on mixed-criticality systems.
The paper aims to safely reduce the cost of mixed-criticality multi-core systems by addressing inefficient usage of memory bandwidth. This is achieved by combining per-core memory access regulation with the well-established Vestal model, which improves on the state-of-the-art in two respects: 1) We allow the memory access budgets of the cores to be dynamically adjusted, when the system undergoes a mode change, reflecting the different needs in each mode, for better schedulability. 2) We devise memory regulation-aware and stall-aware schedulability analysis for such systems, based on AMC-max. By comparison, the state-of-the-art offered no option of dynamic adjustment of core budgets, and only offered regulation-aware schedulability analysis based on AMC-rtb, which is inherently more pessimistic. Finally, 3) we consider different task assignment and bandwidth allocation heuristics, to assess the improvement from the dynamic memory budgets and new analysis. Our results show improvements in schedulability ratio of up to 9.1% over the state-of-the-art.