Maximum Predictability in Signal Interactions With HARETICK Kernel

Micea, Mihai V.; Creţu, Vladimir; Groza, Voicu

doi:10.1109/tim.2006.876530

Cited by 14 publications

(13 citation statements)

References 23 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%

“…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%

“…Considering the system S of hard real-time tasks described by Equation (1), an essential question is how to determine if its operation is feasible according to the H 2 RTS method proposed here. As the FENP tasks in the S FENP subset run in the highest priority execution context, they are schedulable according to the tests described in [ 2 ], without any potential influence other tasks in S might have on the system timing behavior. Thus, the H 2 RTS schedulability problem reduces to finding a feasible schedule to the ε j ( j = 1… n ) tasks in the S MEDF subset over a time interval of arbitrary length, while also considering the corresponding workload required by the FENP tasks over the same interval.…”

Section: Integrated Schedulability Analysis Of H 2 mentioning

confidence: 99%

“…In our view, a carefully designed ensemble made of one static non-preemptive, table driven scheduling algorithm called Fixed Execution Non-preemptive (FENP) algorithm [ 2 ] and one dynamic, derived from classic Earliest-Deadline-First (EDF) algorithm [ 3 ], can ensure the efficiency of the task scheduling mechanism, in terms of flexibility and maximum CPU utilization factor (compared to an approach based only on clock-driven scheduling mechanism), while preserving the determinism and stability of the static schedulers. Moreover, we have designed a new and effective theoretical separation method between the proposed criticality levels, each level having its own execution environment, isolated from the others.…”

Section: Introductionmentioning

confidence: 99%

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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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