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On Bounding Execution Demand under Mixed-Criticality EDF

Published:10 October 2018Publication History

ABSTRACT

This paper is concerned with mixed-criticality systems where a set of low-criticality (LO) and high-criticality (HI) tasks share one processor and are scheduled under the EDF algorithm. Basically, the system operates in two modes: LO and HI mode. In LO mode, one HI task may exceed its execution budget, which then causes a change to HI mode in the system. HI tasks are assigned larger execution budgets in HI mode at the cost of the LO tasks --- which are assumed to be discarded. Since these mode changes may happen at arbitrary points in time, it is difficult to find an accurate bound on the amount of carry-over execution demand. That is the execution demand by HI jobs that were released before, but did not finish executing at the point of changing to HI mode. As a consequence, the resulting characterization of the overall execution demand becomes pessimistic. In this paper, to overcome this problem, a technique is proposed that works around the computation of carry-over execution demand and results in a more accurate bound on execution demand under mixed-criticality EDF. In principle, the proposed technique consists in separating the schedulability analysis of stable HI mode from that of the transition between modes and deriving a separate demand bound function for the latter case. The proposed technique results not only in a considerably simpler, but also tighter bound on execution demand under mixed-criticality EDF, in particular, as the number of HI tasks increases. We illustrate this analytically and by a large set of experiments based on synthetic data.

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        cover image ACM Other conferences
        RTNS '18: Proceedings of the 26th International Conference on Real-Time Networks and Systems
        October 2018
        277 pages
        ISBN:9781450364638
        DOI:10.1145/3273905

        Copyright © 2018 ACM

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        Publication History

        • Published: 10 October 2018

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        Acceptance Rates

        RTNS '18 Paper Acceptance Rate25of52submissions,48%Overall Acceptance Rate119of255submissions,47%

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