Optimised Adaptation of Mixed-Criticality Systems with Periodic Tasks on Uniform Multiprocessors in Case of Faults

Kirner, Raimund; Iacovelli, Saverio; Zolda, Michael

doi:10.1109/isorcw.2015.61

Cited by 3 publications

(6 citation statements)

References 12 publications

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“…Binary search continues on the upper half to find a task set with better tolerance load. On the other hand, if the resulting task set consists of more than one task, then it is used to create an LP problem according to TRTCM model published in [17] with lm used as upper bound for the resource constraint. The LP optimisation gives the optimised periods for each task.…”

Section: Optimisation Methodsmentioning

confidence: 99%

“…TRTCM allows to consider different performance parameters via utility functions such as latency, throughput and jitter and to optimise the Quality of Service (QoS) by maximising the overall system utility in case of standard and mixed-criticality real-time services. Such approach has been further developed for adaptation of mixed-criticality systems with periodic task sets on uniform multiprocessors [17].…”

Section: Related Workmentioning

confidence: 99%

“…Figure 1 also contains the critical period (indicated as p crit ) that represents the arrival rate for which the task utility becomes zero. More details on the tolerance-based real-time model can be found in [17].…”

Section: Utility Functionmentioning

confidence: 99%

See 2 more Smart Citations

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

Iacovelli

Kirner

Menon

2018

2018 IEEE 13th International Symposium on Industrial Embedded Systems (SIES)

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Section: Optimisation Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

Iacovelli

Kirner

Menon

2018

2018 IEEE 13th International Symposium on Industrial Embedded Systems (SIES)

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“…The fundamental concept of our scheduler is the tolerance-based real-time computing model (TRTCM) [13,25]. Instead of using a single performance limit such as a deadline or throughput limit, in TRTCM, a tolerance range is added, which allows a guided search for the best overall system utility in case of resource shortages.…”

Section: Trtcmmentioning

confidence: 99%

ATMP-CA: Optimising Mixed-Criticality Systems Considering Criticality Arithmetic

2021

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Many safety-critical systems use criticality arithmetic, an informal practice of implementing a higher-criticality function by combining several lower-criticality redundant components or tasks. This lowers the cost of development, but existing mixed-criticality schedulers may act incorrectly as they lack the knowledge that the lower-criticality tasks are operating together to implement a single higher-criticality function. In this paper, we propose a solution to this problem by presenting a mixed-criticality mid-term scheduler that considers where criticality arithmetic is used in the system. As this scheduler, which we term ATMP-CA, is a mid-term scheduler, it changes the configuration of the system when needed based on the recent history of deadline misses. We present the results from a series of experiments that show that ATMP-CA’s operation provides a smoother degradation of service compared with reference schedulers that do not consider the use of criticality arithmetic.

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“…A task's criticality can be derived from different aspects. One possibility is to express the relative importance or relative utility of different services in a system as their criticality [5]. Another possibility is to express the relative level of assurance, for example, dictated by different development standards for safety critical or relevant systems, such as DO-178C [6] in the avionics domain, ISO26262 [7] in the automotive domain, or IEC 61508 [8] in the automation domain as different levels of criticality.…”

Section: Introductionmentioning

confidence: 99%

A Lazy Bailout Approach for Dual-Criticality Systems on Uniprocessor Platforms

Iacovelli

Kirner

2019

Designs

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A challenge in the design of cyber-physical systems is to integrate the scheduling of tasks of different criticality, while still providing service guarantees for the higher critical tasks in the case of resource-shortages caused by faults. While standard real-time scheduling is agnostic to the criticality of tasks, the scheduling of tasks with different criticalities is called mixed-criticality scheduling. In this paper, we present the Lazy Bailout Protocol (LBP), a mixed-criticality scheduling method where low-criticality jobs overrunning their time budget cannot threaten the timeliness of high-criticality jobs while at the same time the method tries to complete as many low-criticality jobs as possible. The key principle of LBP is instead of immediately abandoning low-criticality jobs when a high-criticality job overruns its optimistic WCET estimate, to put them in a low-priority queue for later execution. To compare mixed-criticality scheduling methods, we introduce a formal quality criterion for mixed-criticality scheduling, which, above all else, compares schedulability of high-criticality jobs and only afterwards the schedulability of low-criticality jobs. Based on this criterion, we prove that LBP behaves better than the original Bailout Protocol (BP). We show that LBP can be further improved by slack time exploitation and by gain time collection at runtime, resulting in LBPSG. We also show that these improvements of LBP perform better than the analogous improvements based on BP.

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Optimised Adaptation of Mixed-Criticality Systems with Periodic Tasks on Uniform Multiprocessors in Case of Faults

Cited by 3 publications

References 12 publications

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

ATMP: An Adaptive Tolerance-based Mixed-criticality Protocol for Multi-core Systems

ATMP-CA: Optimising Mixed-Criticality Systems Considering Criticality Arithmetic

A Lazy Bailout Approach for Dual-Criticality Systems on Uniprocessor Platforms

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