Availability enhancement and analysis for mixed-criticality systems on multi-core

Medina, Roberto; Borde, Étienne; Pautet, Laurent

doi:10.23919/date.2018.8342210

Cited by 12 publications

(55 citation statements)

References 14 publications

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“…As shown in Fig. 8, the QoS for methods of [22], [33] in Scenario 1 is higher than the QoS for our proposed method in total (according to the Cumulative Distribution Function (CDF) line). However, in this scenario, the TDP constraint is violated several times due to the execution of HC tasks in parallel on cores, and there is no policy to manage the peak power.…”

Section: )mentioning

confidence: 81%

“…Fig. 1 shows the task graph of Unmanned Air Vehicle (UAV), which is a real-life MC application task graph [22]. This application is composed of eight tasks.…”

Section: System Models and Problem Definition A Mixed-criticality Task Modelmentioning

confidence: 99%

“…In Section III-A, we have defined the QoS as the successfully executed LC tasks to all LC tasks. However, we use three different definitions of QoS to evaluate the methods of [22], [23], [33] more accurately, as follows.…”

Section: )mentioning

confidence: 99%

“…However, in this scenario, the TDP constraint is violated several times due to the execution of HC tasks in parallel on cores, and there is no policy to manage the peak power. Moreover, for the second scenario in the methods of [22], [33], the figure shows that in 22.5% of task sets, the TDP constraint is violated while executing some HC tasks on cores. Besides, the QoS in the second scenario for [23] is zero, due to dropping all LC tasks in the HI mode.…”

Section: )mentioning

confidence: 99%

“…Besides, the QoS in the second scenario for [23] is zero, due to dropping all LC tasks in the HI mode. Now, if we investigate the methods of [22], [23], [33] in the third scenario, the QoS of [22], [33] is more than the QoS of [23] due to the executing LC tasks in the HI mode. However, they have less QoS in this scenario compared to our proposed method.…”

Section: )mentioning

confidence: 99%

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Toward the Design of Fault-Tolerance-Aware and Peak-Power-Aware Multicore Mixed-Criticality Systems

Ranjbar

Hosseinghorban

Salehi

et al. 2022

IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst.

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Mixed-Criticality (MC) systems have recently been devised to address the requirements of real-time systems in industrial applications, where the system runs tasks with different criticality levels on a single platform. In some workloads, a highcritically task might overrun and overload the system, or a fault can occur during the execution. However, these systems must be fault-tolerant and guarantee the correct execution of all highcriticality tasks by their deadlines to avoid catastrophic consequences, in any situation. Furthermore, in these MC systems, the peak power consumption of the system may increase, especially in an overload situation and exceed the processor Thermal Design Power (TDP) constraint. This may cause generating heat beyond the cooling capacity, resulting the system stop to avoid excessive heat and halting the processor. In this paper, we propose a technique for dependent dual-criticality tasks in fault-tolerant multi-core MC systems to manage peak power consumption and temperature. The technique develops a tree of possible task mapping and scheduling at design-time to cover all possible scenarios and reduce the low-criticality task drop rate in the highcriticality mode. At run-time, the system exploits the tree to select a proper schedule according to fault occurrences and criticality mode changes. Experimental results show that the average task schedulability is 74.14% on average for the proposed method, while the peak power consumption and maximum temperature are improved by 16.65% and 14.9 • C on average, respectively, compared to a recent work. In addition, for a real-life application, our method reduces the peak power and maximum temperature by up to 20.06% and 5 • C, respectively, compared to a state-ofthe-art approach.

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Section: )mentioning

confidence: 81%

“…Fig. 1 shows the task graph of Unmanned Air Vehicle (UAV), which is a real-life MC application task graph [22]. This application is composed of eight tasks.…”

Section: System Models and Problem Definition A Mixed-criticality Task Modelmentioning

confidence: 99%