Current hard real-time scheduling and analysis techniques are unable to efficiently utilize the computational bandwidth provided by multicore platforms. This is due to the large gap between worst-case execution time predictions used in schedulability analysis and actual execution times seen in practice. In this paper, we view this gap as "slack" that can be accounted for during schedulability analysis and reclaimed for less critical work. We use this technique to develop an architecture for scheduling mixed-criticality real-time workloads on multiprocessor platforms. Our architecture provides temporal isolation among tasks of different criticalities while allowing slack to be redistributed across criticality levels.
Existing research in soft real-time scheduling has focused on determining tardiness bounds given a scheduling algorithm. In this paper, we study lateness bounds, which are related to tardiness bounds, and propose a scheduling algorithm to minimize lateness bounds, namely the global fair lateness
Abstract. The Earliest Deadline First (EDF) scheduling algorithm is known to be suboptimal for meeting all deadlines under global scheduling on multiprocessor platforms. However, EDF is an attractive choice for scheduling soft-real-time systems on multiprocessors. Previous work has demonstrated that the maximum tardiness is bounded, and has derived formulas for computing tardiness bounds, in EDF-scheduled real-time systems that can be modeled as collections of recurrent tasks modeled using the well-known implicit-deadline (Liu and Layland) task model. This research extends the applicability of previous techniques to systems that are modeled using the more general arbitrary sporadic task model. It also improves on prior work even for implicit-deadline systems. An algorithm is derived here that computes tardiness bounds in polynomial time. Previously, these bounds could only have been approximated in sub-exponential time.
Semi-partitioned real-time scheduling algorithms extend partitioned ones by allowing a (usually small) subset of tasks to migrate. The first such algorithm to be proposed was directed at soft real-time (SRT) sporadic task systems where bounded deadline tardiness is acceptable. That algorithm, called EDF-fm, is able to fully utilize the underlying hardware platform's available capacity. Moreover, it has the desirable practical property that migrations are boundary-limited, i.e., they can only occur at job boundaries. Unfortunately, EDF-fm requires restrictions on pertask utilizations, and thus is not optimal. In this paper, a new boundary-limited, semi-partitioned algorithm is presented for SRT systems that is the first such algorithm to be optimal. This algorithm, called EDF-os, is similar to EDF-fm but utilizes several new mechanisms that obviate the need for per-task utilization restrictions. Experiments presented herein show that, not only is EDF-os provably better than EDF-fm with respect to schedulability, tardiness bounds under EDF-os are often much lower as well.
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