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Title: Multi-rate fluid scheduling of mixed-criticality systems on multiprocessors
Authors: Ramanathan, Saravanan
Easwaran, Arvind
Cho, Hyeonjoong
Keywords: Mixed-criticality
Implicit-deadline Sporadic Tasks
Issue Date: 2017
Source: Ramanathan, S., Easwaran, A., & Cho, H. (2018). Multi-rate fluid scheduling of mixed-criticality systems on multiprocessors. Real-Time Systems, 54(2), 247-277.
Series/Report no.: Real-Time Systems
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.
ISSN: 0922-6443
DOI: 10.1007/s11241-017-9296-1
Rights: © 2017 Springer Science+Business Media, LLC. This is the author created version of a work that has been peer reviewed and accepted for publication by Real-Time Systems, Springer Science+Business Media, LLC. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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