Measuring the Performance of Schedulability Tests

Bini, Enrico; Buttazzo, Giorgio

doi:10.1007/s11241-005-0507-9

Cited by 706 publications

(343 citation statements)

References 17 publications

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“…Experimental setup To evaluate the theoretical scheduling effectiveness of the approaches presented, we apply the respective offline schedulability tests to synthetic task sets, whose generation is controlled with the following parameters: -L-mode utilisations (U L i ): Generated using the UUnifast-discard algorithm [14] …”

Section: Discussionmentioning

confidence: 99%

Semi-partitioned Mixed-Criticality Scheduling

Awan

Bletsas

Souto

et al. 2017

Architecture of Computing Systems - ARCS 2017

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Scheduling isolation in mixed-criticality systems is challenging without sacrificing performance. In response, we propose a scheduling approach that combines server-based semi-partitioning and deadline scaling. Semipartitioning (whereby only some tasks migrate, in a carefully managed manner), hitherto used in single criticality systems, offers good performance with low overheads. Deadline-scaling selectivelyprioritizes high-criticality tasks in parts of the schedule to ensure theirdeadlines are met even in rares case of execution time overrun. Ournew algorithm NPS-F-MC brings semi-partitioning to mixed-criticalityscheduling and uses Ekberg and Yi 19s state-ofthe-art deadline scaling approach. It ensures scheduling isolation among different-criticality tasksand only allows low-criticality task migration. We also explore variantsthat disallow migration entirely or relax the isolation between differentcriticalities (SP-EKB) in order to evaluate the performance tradeoffs associated with more flexible or rigid safety and isolation requirements. Semi-partitioned mixed-criticality schedulingMuhammad Ali Awan * + , Konstantinos Bletsas * + , Pedro F. Souto ‡ * and Eduardo Tovar * + * CISTER/INESC-TEC Research Centre, Porto, Portugal + ISEP/IPP, Porto ‡ Faculty of Engineering, University of Porto Abstract. Scheduling isolation in mixed-criticality systems is challenging without sacrificing performance. In response, we propose a scheduling approach that combines server-based semi-partitioning and deadlinescaling. Semi-partitioning (whereby only some tasks migrate, in a carefully managed manner), hitherto used in single criticality systems, offers good performance with low overheads. Deadline-scaling selectively prioritise high-criticality tasks in parts of the schedule to ensure their deadlines are met even in rares case of execution time overrun. Our new algorithm NPS-F-MC brings semi-partitioning to mixed-criticality scheduling and uses Ekberg and Yi's state-of-the-art deadline scaling approach. It ensures scheduling isolation among different-criticality tasks and only allows low-criticality task migration. We also explore variants that disallow migration entirely or relax the isolation between different criticalities (SP-EKB) in order to evaluate the performance tradeoffs associated with more flexible or rigid safety and isolation requirements.

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Section: Discussionmentioning

confidence: 99%

Semi-partitioned Mixed-Criticality Scheduling

Awan

Bletsas

Souto

et al. 2017

Architecture of Computing Systems - ARCS 2017

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“…-The task utilizations were generated using UUnifast (Bini and Buttazzo 2005) with an equal utilization assumed for each core. -Task periods were set based on task utilization and base WCET, i.e., T i = C i /U i .…”

Section: Task Set Generationmentioning

confidence: 99%

An extensible framework for multicore response time analysis

et al. 2017

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In this paper, we introduce a multicore response time analysis (MRTA) framework, which decouples response time analysis from a reliance on contextindependent WCET values. Instead, the analysis formulates response times directly The additional material includes: Section 4: analysis for warmed-up caches and dynamic scratchpads (Sects. 4.3 and 4.2). Section 7: extensions to the task model, including RTOS and interrupts, shared software resources, and open systems and incremental verification. Section 8: presentation of a cycle-accurate multicore simulator. Section 9: evaluation of different local memory types (Sect. 9.2), a comparison between predictable and reference architectures (Sect. 9.3), and a verification of the precision of the analysis using results from the simulator (Sect. 9.4). 123Real-Time Syst from the demands placed on different hardware resources. The MRTA framework is extensible to different multicore architectures, with a variety of arbitration policies for the common interconnects, and different types and arrangements of local memory. We instantiate the framework for single level local data and instruction memories (cache or scratchpads), for a variety of memory bus arbitration policies, including: Round-Robin, FIFO, Fixed-Priority, Processor-Priority, and TDMA, and account for DRAM refreshes. The MRTA framework provides a general approach to timing verification for multicore systems that is parametric in the hardware configuration and so can be used at the architectural design stage to compare the guaranteed levels of real-time performance that can be obtained with different hardware configurations. We use the framework in this way to evaluate the performance of multicore systems with a variety of different architectural components and policies. These results are then used to compose a predictable architecture, which is compared against a reference architecture designed for good average-case behaviour. This comparison shows that the predictable architecture has substantially better guaranteed real-time performance, with the precision of the analysis verified using cycle-accurate simulation.

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“…The deadlines were implicit. 2) Execution Times -LO-criticality utilisation U (LO) values for each task where determined according to the Uunifast algorithm [10], thus ensuring an unbiased distribution of values that sum to the target utilisation for the system. LO-criticality execution times were then set to C(LO) = U (LO).T , and HI-criticality execution times to C(HI) = CF.C(LO) where CF is the criticality factor (CF = 2.0).…”

Section: B Experimental Frameworkmentioning

confidence: 99%

A Bailout Protocol for Mixed Criticality Systems

Bate

Burns

Davis

2015

2015 27th Euromicro Conference on Real-Time Systems

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Abstract-To move mixed criticality research into industrial practice requires models whose run-time behaviour is acceptable to systems engineers. Certain aspects of current models, such as abandoning lower criticality tasks when certain situations arise, do not give the robustness required in application domains such as the automotive and aerospace industries. In this paper a new bailout protocol is developed that still guarantees high criticality tasks but minimises the negative impact on lower criticality tasks via a timely return to normal operation. We show how the bailout protocol can be integrated with existing techniques, utilising offline slack to further improve performance. Static analysis is provided for the strong schedulability guarantees, while scenariobased evaluation via simulation is used to explore the effectiveness of the protocol.

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Measuring the Performance of Schedulability Tests

Cited by 706 publications

References 17 publications

Semi-partitioned Mixed-Criticality Scheduling

Semi-partitioned Mixed-Criticality Scheduling

An extensible framework for multicore response time analysis

A Bailout Protocol for Mixed Criticality Systems

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