Quasi-partitioned scheduling: optimality and adaptation in multiprocessor real-time systems

Massa, Ernesto; Lima, George; Regnier, Paul; Levin, Greg; Brandt, Scott

doi:10.1007/s11241-016-9251-6

Cited by 20 publications

(4 citation statements)

References 18 publications

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“…The resulting schedule generates a small number of preemptions and migrations. QPS (Quasi-Partitioned Scheduling) [31] partitions the system tasks into minor and major execution sets, depending on whether they require one or multiple processors. QPS boils down to a partitioned EDF in the case of minor sets, whereas major sets are scheduled either by a set of QPS servers on multiple processors, or by local EDF scheduler on a single processor depending on execution requirements.…”

Section: Related Workmentioning

confidence: 99%

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Maximizing Utilization and Minimizing Migration in Thermal-Aware Energy-Efficient Real-Time Multiprocessor Scheduling

et al. 2021

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This work proposes CAlECs, a clustered scheduling system for MPSoCs subject to thermal and energy constraints. It calculates off-line a cyclic executive honoring temporal and thermal constraints, for a hard real-time (HRT) task set at minimum frequency to reduce consumed energy, minimizing context switches and migrations. It also provides an on-line controller able to manage system and task parametric variations and soft real-time (SRT) tasks, always meeting the HRT task set constraints and the system thermal bound. CAlECS maximizes CPU utilization to help avoid overprovisioning contributing to a low SWaP factor. Its modular design allows the utilization of different modeling and scheduling approaches, and makes the off-line and on-line components independent from each other to better suit the requirements of a specific system. We experimentally show that the cyclic executive provided by CAlECS for HRT task sets outperforms RUN, a reference off-line algorithm in terms of optimal number of context switches.

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Section: Related Workmentioning

confidence: 99%

“…Thus, their complexity is O(1), because it requires to solve Eqs. (31) and (35), that have a fixed number of operations. A different implementation approach may use a devoted CP U for the feedback controller routine.…”

Section: B On-line Computationsmentioning

confidence: 99%

Maximizing Utilization and Minimizing Migration in Thermal-Aware Energy-Efficient Real-Time Multiprocessor Scheduling

et al. 2021

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“…However, most of optimal global scheduling algorithms excessively chop o the tasks' execution causing unecessary runtime overhead. More recently, better approaches in terms of reduced overheads have been proposed, namely Reduction to UNiprocessor (RUN) (REGNIER et al, 2011), Quasi-Partitioned Scheduling (QPS) (MASSA et al, 2016) and Unfair Earliest Deadline First (U-EDF) (NELISSEN et al, 2012). These achieve optimality without causing too many preemptions and task migrations between processors as compared to previous algorithms.…”

Section: Scheduling Algorithmsmentioning

confidence: 99%

“…as a means of obtaining optimality with reduced runtime overheads, namely Reduction to UNiprocessor (RUN) (REGNIER et al, 2011), Quasi-Partitioning Scheduling (QPS) (MASSA et al, 2016), and Unfair EDF (U-EDF) (NELISSEN et al, 2012) denoting the numbers of task and processors respectively. This may be a point of concern for some large systems in terms of runtime overhead.…”

Section: Scheduling Algorithmsmentioning

confidence: 99%

Shared resources in multiprocessor real-time systems scheduled by RUN

Teixeira

Lima

2021

Real-Time Syst

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A hard real-time system can be defined as the one that at least one of its tasks must meet its deadlines whenever the system is running. This requirement makes the scheduling algorithm a key element for system correctness. Ideally, the scheduling algorithm employed must both exhibit low overhead (efficiency) and ensure that no task deadline is missed whenever this can be ensured by some scheduling algorithm (optimality). RUN (Reduction to Uniprocessor) is an algorithm capable of efficiently and optimally scheduling a set of strictly periodic tasks on a multiprocessor platform when tasks do not share any resources but processors. Although it has already been shown that RUN is compatible with resource sharing, the only existing solution prevents preemptive access to shared resources. Unlike this approach, which can be considered too restrictive due to its poor schedulability, we used MrsP (Multiprocessor resource sharing Protocol) as a more flexible resource sharing mechanism. Making the rules of both RUN and MrsP compatible to each other was thus our main goal. The derived solution was implemented on Linux Textbed for Multiprocessor Scheduling in Real-Time systems (Litmus-RT), namely a Linux-based real-time operating system. We proposed a new task packaging heuristic and performed experimental evaluations comparing our solution with the existing one. The results showed that the proposed solution presented better results in terms of schedulability, total overhead and number of migrations and preemptions.

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