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Optimal priority and threshold assignment for fixed-priority preemption threshold scheduling

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Published:20 March 2018Publication History
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Abstract

Fixed-priority preemption-threshold scheduling (FPTS) is a generalization of fixed-priority preemptive scheduling (FPPS) and fixed-priority non-preemptive scheduling (FPNS). Since FPPS and FPNS are incomparable in terms of potential schedulability, FPTS has the advantage that it can schedule any task set schedulable by FPPS or FPNS and some that are not schedulable by either. FPTS is based on the idea that each task is assigned a priority and a preemption threshold. While tasks are admitted into the system according to their priorities, they can only be preempted by tasks that have priority higher than the preemption threshold.

This paper presents a new optimal priority and preemption threshold assignment (OPTA) algorithm for FPTS which in general outperforms the existing algorithms in terms of the size of the explored state-space and the total number of worst case response time calculations performed. The algorithm is based on back-tracking, i.e. it traverses the space of potential priorities and preemption thresholds, while pruning infeasible paths, and returns the first assignment deemed schedulable.

We present the evaluation results where we compare the complexity of the new algorithm with the existing one. We show that the new algorithm significantly reduces the time needed to find a solution. Through a comparative evaluation, we show the improvements that can be achieved in terms of schedulability ratio by our OPTA compared to a deadline monotonic priority assignment.

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        cover image ACM SIGBED Review
        ACM SIGBED Review  Volume 15, Issue 1
        Special Issue on Embedded Operating Systems Workshop (EWiLi '16)
        February 2018
        56 pages
        EISSN:1551-3688
        DOI:10.1145/3199610
        Issue’s Table of Contents

        Copyright © 2018 Authors

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        Association for Computing Machinery

        New York, NY, United States

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        • Published: 20 March 2018

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