Abstract
We consider the partitioned scheduling of sporadic, hard-real-time tasks on a multiprocessor platform with static-priority scheduling policies. Most previous work on the static-priority scheduling of sporadic tasks upon multiprocessors has assumed implicit deadlines (i.e. a task's relative deadline is equal to its period). We relax the equality constraint on a task's deadline and consider task systems with constrained deadlines (i.e. relative deadlines are at most periods). In particular, we consider the first-fit decreasing partitioning algorithm. Since the partitioning problem is easily seen to be NP-hard in the strong sense, this algorithm is unlikely to be optimal. We quantitatively characterize the partitioning algorithm's worst-case performance in terms of resource augmentation.
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