  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.
