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Optimal Semi-Partitioned Scheduling in Soft Real-Time Systems

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Abstract

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, has the desirable property that migrations are boundary-limited, i.e., they can only occur at job boundaries. However, it is not optimal because per-task utilization restrictions are required. In this paper, a new optimal semi-partitioned scheduling algorithm for SRT sporadic task systems is proposed that eliminates such restrictions. This algorithm, called EDF-os, preserves the boundary-limited property. In overhead-aware schedulability experiments presented herein, EDF-os proved to be better than all other tested alternatives in terms of schedulability in almost all considered scenarios. It also proved capable of ensuring very low tardiness bounds, which were near zero in most considered scenarios.

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Notes

  1. 1 Mills and Anderson [32] have shown that the worst-case execution times pertaining to our model can be viewed as operating-system-enforced budgets that can be provisioned on an average-case (or near-average-case) basis. Stochastic analysis pertaining to such a provisioning is layered “on top of” tardiness analysis pertaining to (deterministic) budget allocations.

  2. 2 In prior studies, e.g., [9, 10], average-case overheads were considered when evaluating SRT schedulers, and worst-case overheads when evaluating HRT schedulers.

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Acknowledgments

Work supported by NSF grants CNS 1016954, CNS 1115284, CNS 1218693, and CNS 1239135; and ARO grant W911NF-09-1-0535.

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Correspondence to Jeremy P. Erickson.

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Jeremy Erickson is now employed by Google, Inc.

Appendix

Appendix

1.1 Notation

Table 1

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Anderson, J.H., Erickson, J.P., Devi, U.C. et al. Optimal Semi-Partitioned Scheduling in Soft Real-Time Systems. J Sign Process Syst 84, 3–23 (2016). https://doi.org/10.1007/s11265-015-0983-7

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