Quantifying the Exact Sub-optimality of Non-preemptive Scheduling

Davis, Robert I.; Thekkilakattil, Abhilash; Gettings, Oliver; Dobrin, Radu; Punnekkat, Sasikumar

doi:10.1109/rtss.2015.17

Cited by 7 publications

(8 citation statements)

References 32 publications

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“…Finally, we note that the exact speedup factors for arbitrary deadline task sets derived for the comparisons between FP-NP and FP-P and between FP-NP and EDF-P by Davis et al in [14] also hold in the case where (non-optimal) DM priority assignment and a linear time sufficient schedulability test are used for FP-NP. Thus DM priority assignment combined with a linear-time sufficient test is also speedup optimal when comparing non-preemptive versus preemptive scheduling paradigms.…”

Section: Discussionmentioning

confidence: 78%

Exact speedup factors for linear-time schedulability tests for fixed-priority preemptive and non-preemptive scheduling

Brüggen

Chen

Davis

et al. 2017

Information Processing Letters

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In this paper, we investigate the quality of several linear-time schedulability tests for preemptive and non-preemptive fixed-priority scheduling of uniprocessor systems. The metric used to assess the quality of these tests is the resource augmentation bound commonly known as the processor speedup factor. The speedup factor of a schedulability test corresponds to the smallest factor by which the processing speed of a uniprocessor needs to be increased such that any task set that is feasible under an optimal preemptive (non-preemptive) work-conserving scheduling algorithm is guaranteed to be schedulable with preemptive (non-preemptive) fixed priority scheduling if this scheduling test is used, assuming an appropriate priority assignment. We show the surprising result that the exact speedup factors for Deadline Monotonic (DM) priority assignment combined with sufficient linear-time schedulability tests for implicit-, constrained-, and arbitrary-deadline task sets are the same as those obtained for optimal priority assignment policies combined with exact schedulability tests. Thus in terms of the speedup-factors required, there is no penalty in using DM priority assignment and simple linear schedulability tests.

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Section: Discussionmentioning

confidence: 78%

Exact speedup factors for linear-time schedulability tests for fixed-priority preemptive and non-preemptive scheduling

Brüggen

Chen

Davis

et al. 2017

Information Processing Letters

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“…Preliminary publication: This paper extends initial research into speedup factors for preemptive versus non-preemptive uniprocessor scheduling published in RTSS 2015 (Davis et al 2015c). The main extension is the proof of the exact speedup factor required to guarantee the FP-P feasibility of any FP-NP feasible constrained-deadline task set.…”

mentioning

confidence: 90%

“…In this paper, we investigate the suboptimality of fixed priority non-preemptive scheduling. Specifically, we derive the exact processor speed-up factor required to guarantee the feasibility under FP-NP (i.e.Preliminary publication: This paper extends initial research into speedup factors for preemptive versus non-preemptive uniprocessor scheduling published in RTSS 2015 (Davis et al 2015c). The main extension is the proof of the exact speedup factor required to guarantee the FP-P feasibility of any FP-NP feasible constrained-deadline task set.…”

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confidence: 99%

Exact speedup factors and sub-optimality for non-preemptive scheduling

et al. 2017

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Fixed priority scheduling is used in many real-time systems; however, both preemptive and non-preemptive variants (FP-P and FP-NP) are known to be sub-optimal when compared to an optimal uniprocessor scheduling algorithm such as preemptive earliest deadline first (EDF-P). In this paper, we investigate the suboptimality of fixed priority non-preemptive scheduling. Specifically, we derive the exact processor speed-up factor required to guarantee the feasibility under FP-NP (i.e.Preliminary publication: This paper extends initial research into speedup factors for preemptive versus non-preemptive uniprocessor scheduling published in RTSS 2015 (Davis et al. 2015c). The main extension is the proof of the exact speedup factor required to guarantee the FP-P feasibility of any FP-NP feasible constrained-deadline task set. Real-Time Syst (2018) 54:208-246 209 schedulability assuming an optimal priority assignment) of any task set that is feasible under EDF-P. As a consequence of this work, we also derive a lower bound on the sub-optimality of non-preemptive EDF (EDF-NP). As this lower bound matches a recently published upper bound for the same quantity, it closes the exact sub-optimality for EDF-NP. It is known that neither preemptive, nor non-preemptive fixed priority scheduling dominates the other, in other words, there are task sets that are feasible on a processor of unit speed under FP-P that are not feasible under FP-NP and viceversa. Hence comparing these two algorithms, there are non-trivial speedup factors in both directions. We derive the exact speed-up factor required to guarantee the FP-NP feasibility of any FP-P feasible task set. Further, we derive the exact speed-up factor required to guarantee FP-P feasibility of any constrained-deadline FP-NP feasible task set.

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“…provides a measure of the sub-optimality of algorithm B. Speedup factors have previously been derived for the classic sporadic task model, comparing fixed priority and EDF scheduling under both preemptive and non-preemptive paradigms [18], [17], [19]. To the best of our knowledge, this is the first time that such measures have been derived for the M/C scheduling problem.…”

Section: S Chedulability Analysismentioning

confidence: 99%

Exact Response Time Analysis for Fixed Priority Memory-Processor Co-Scheduling

Melani

Bertogna²,

Davis³

et al. 2017

IEEE Trans. Comput.

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Recent technological advances have led to an increasing gap between memory and processor performance, since memory bandwidth is progressing at a much slower pace than processor bandwidth. Pre-fetching techniques are traditionally used to bridge this gap and achieve high processor utilization while tolerating high memory latencies. Following this trend, new computational models have been proposed to split task execution in two consecutive phases: a memory phase in which the required instructions and data are pre-fetched to local memory (M-phase), and an execution phase in which the task is executed with no memory contention (C-phase). Decoupling memory and execution phases not only simplifies the timing analysis, but also allows a more efficient (and predictable) pipelining of memory and execution phases through proper co-scheduling algorithms. This paper takes a further step towards the design of smart co-scheduling algorithms for sporadic real-time tasks complying with the memory-computation (M/C) model, by proposing a theoretical framework aimed at tightly characterizing the schedulability improvement obtainable with the adopted M/C task model on single-core systems. In particular, a critical instant is identified for M/C tasks scheduled with fixed priority and an exact response time analysis with pseudo-polynomial complexity is provided. Then, we investigate the problem of priority assignment for M/C tasks, showing that a necessary condition to achieve optimality is to allow different priorities for the two phases. Our experiments show that the proposed techniques provide a significant schedulability improvement with respect to classic execution models, placing an important building block towards the design of more efficient partitioned multi-core systems

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Quantifying the Exact Sub-optimality of Non-preemptive Scheduling

Cited by 7 publications

References 32 publications

Exact speedup factors for linear-time schedulability tests for fixed-priority preemptive and non-preemptive scheduling

Exact speedup factors for linear-time schedulability tests for fixed-priority preemptive and non-preemptive scheduling

Exact speedup factors and sub-optimality for non-preemptive scheduling

Exact Response Time Analysis for Fixed Priority Memory-Processor Co-Scheduling

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