Leveraging Mixed Criticality Task Budgets

In mixed-criticality systems, classical models assume an estimated execution time budget for tasks in each possible criticality, and when a job presents a budget overrun, they tend to drop the lower criticality tasks to preserve the schedulability of the higher criticality tasks. However, few studies focus on how the different execution time budgets are calculated, and it has been emphasized that tasks of lower criticality must provide a minimum service for the system to function properly. In this paper, we present a greedy heuristic for calculating the execution time budget to be allocated to real-time tasks according to their criticality and the shape of their execution time distribution. This budget is calculated with the aim of minimizing potential budget overruns. We first introduce a new statistical dispersion parameter called the maximum coefficient of variation (VWCET). This parameter describes the tendency of execution times towards the worst-case execution time and can be adjusted according to the criticality of the task. We show through experiments that the proposed heuristic reduces the probability of exceeding the time budget allocated to the task, and improves the performance of low-criticality tasks.