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Real-Time Systems

, Volume 54, Issue 2, pp 247–277 | Cite as

Multi-rate fluid scheduling of mixed-criticality systems on multiprocessors

  • Saravanan Ramanathan
  • Arvind Easwaran
  • Hyeonjoong Cho
Article
  • 172 Downloads

Abstract

In this paper we consider the problem of mixed-criticality (MC) scheduling of implicit-deadline sporadic task systems on a homogenous multiprocessor platform. Focusing on dual-criticality systems, algorithms based on the fluid scheduling model have been proposed in the past. These algorithms use a dual-rate execution model for each high-criticality task depending on the system mode. Once the system switches to the high-criticality mode, the execution rates of such tasks are increased to meet their increased demand. Although these algorithms are speed-up optimal, they are unable to schedule several feasible dual-criticality task systems. This is because a single fixed execution rate for each high-criticality task after the mode switch is not efficient to handle the high variability in demand during the transition period immediately following the mode switch. This demand variability exists as long as the carry-over jobs of high-criticality tasks, that is jobs released before the mode switch, have not completed. Addressing this shortcoming, we propose a multi-rate fluid execution model for dual-criticality task systems in this paper. Under this model, high-criticality tasks are allocated varying execution rates in the transition period after the mode switch to efficiently handle the demand variability. We derive a sufficient schedulability test for the proposed model and show its dominance over the dual-rate fluid execution model. Further, we also present a speed-up optimal rate assignment strategy for the multi-rate model, and experimentally show that the proposed model outperforms all the existing MC scheduling algorithms with known speed-up bounds.

Keywords

Mixed-criticality Implicit-deadline sporadic tasks Multiprocessors Fluid scheduling 

Notes

Acknowledgements

We would like to thank Jaewoo Lee for providing motivation for this work through discussions on the sub-optimality of dual-rate fluid scheduling. This research was funded in part by the Ministry of Education, Singapore, Tier-1 Grant RG21/13 and Tier-2 Grant ARC9/14, and by the Start-Up-Grant from SCSE, NTU, Singapore. This research was also partly supported by Basic Science Research Program of the National Research Foundation of Korea (NRF-2015R1D1A1A01057018)

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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.Department of Computer and Information ScienceKorea UniversitySeoulSouth Korea

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