Highly predictable execution support for critical applications with HARETICK kernel

Micea, Mihai V.; Creţu, Vladimir

doi:10.1016/j.aeue.2005.05.011

Cited by 9 publications

(4 citation statements)

References 18 publications

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“…The Fixed Execution Non-Preemptive (FENP) algorithm [ 2 ] has been designed to provide maximum predictability for the execution in a high-priority, non-preemptive context, of periodic tasks with the highest criticality. It has been implemented on the HARETICK kernel [ 27 ] and used in various real-time signal acquisition, processing and data communication applications which require perfectly synchronized interactions with signals [ 28 , 29 ].…”

Section: H 2 Rts: the Hybrid Hard Real-time Schmentioning

confidence: 99%

“…The schedulability analysis is based on an efficient offline test, which also determines the relative start time (phase φ i ) of each task μ i in S FENP , if the subset has been found feasible [ 2 ]. Even though the FENP has been developed for (perfectly) periodic tasks, the algorithm can also be used for scheduling sporadic tasks using the so-called “Ghost ModXs” or “ghost jobs”, which are defined and described in [ 27 ].…”

Section: H 2 Rts: the Hybrid Hard Real-time Schmentioning

confidence: 99%

“…First, there is its lack of flexibility, as with the case of all the fixed-priority algorithms which statically assign the priority of tasks at the offline analysis phase, based on their respective time parameters. The “ghost job” and “execution counter” mechanisms [ 27 ] provide a partial solution by solving the case in which a period of a task needs to be modified at runtime by multiples of the initial period. The second shortcoming of the FENP algorithm is its lack of efficiency regarding the maximum total processor utilization factor, which is typically below 70%.…”

Section: H 2 Rts: the Hybrid Hard Real-time Schmentioning

confidence: 99%

“…Therefore it is added to the computational cost ( C i ) of each task μ i ( i = 1, …, m ) at the offline schedulability analysis phase. A detailed discussion of the FENP runtime mechanisms, including implementation-specific values and experimental measurements, is provided in [ 2 , 27 ]. MEDF execution context is supported by the online scheduling module, which is called upon the completion of each MEDF job.…”

Section: H 2 Rts: the Hybrid Hard Real-time Schmentioning

confidence: 99%

See 3 more Smart Citations

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

Micea

Stangaciu

et al. 2017

Sensors

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Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

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