The partitioned, static-priority scheduling of sporadic real-time tasks with constrained deadlines on multiprocessor platforms

Abstract

We consider the partitioned scheduling of sporadic, hard-realtime 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. © Springer-Verlag Berlin Heidelberg 2006.