Bounding and shaping the demand of generalized mixed-criticality sporadic task systems

Abstract

We generalize the commonly used mixed-criticality sporadic task model to let all task parameters (execution-time, deadline and period) change between criticality modes. In addition, new tasks may be added in higher criticality modes and the modes may be arranged using any directed acyclic graph, where the nodes represent the different criticality modes and the edges the possible mode switches. We formulate demand bound functions for mixed-criticality sporadic tasks and use these to determine EDF-schedulability. Tasks have different demand bound functions for each criticality mode. We show how to shift execution demand between different criticality modes by tuning the relative deadlines. This allows us to shape the demand characteristics of each task. We propose efficient algorithms for tuning all relative deadlines of a task set in order to shape the total demand to the available supply of the computing platform. Experiments indicate that this approach is successful in practice. This new approach has the added benefit of supporting hierarchical scheduling frameworks.