Strategies that artificially tighten high-criticality task deadlines in low-criticality behaviors have been successfully employed for scheduling mixed-criticality systems. Although efficient scheduling algorithms have been developed for implicit deadline task systems, the same is not true for more general sporadic tasks. In this paper we develop a new demand-based schedulability test for such general mixed-criticality task systems, in which we collectively bound the low- and high-criticality demand of tasks. We show that the new test strictly dominates the only other known demand-based test for such systems. We also propose a new deadline tightening strategy based on this test, and show through simulations that the strategy significantly outperforms all known scheduling algorithms for a variety of sporadic task systems.
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