An Open Ravenscar Real-Time Kernel for GNAT

Puente, Juan Antonio de la; Ruiz, José Antonio Camúñez; Zamorano, Juan

doi:10.1007/10722060_4

Cited by 35 publications

(14 citation statements)

References 10 publications

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“…The GNATforLEON compilation chain (Ruiz, 2005) is being used, together with additional tools supporting testing and some kinds of static analysis in order to facilitate validation. The application software runs on top of the GNAT run-time library (GNARL) and the ORK+ realtime kernel, which is developed and maintained by the UPM team (de la Puente et al, 2000).…”

Section: • Telecommand and Telemetry (Tc/tm)mentioning

confidence: 99%

Safety Concept for a Mixed Criticality On-Board Software System ∗

et al. 2015

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This paper presents a safety concept for the on-board software system of the UPMSat-2 experimental satellite. Subsystems with different criticality levels are assigned to different partitions in a partitioned software architecture. The architecture is based on XtratuM, an open-source virtualization kernel, and ORK+, an open-source real-time kernel for highintegrity systems. The safety requirements of the system are analysed, and a safety concept is developed based on the partitioned software architecture. The properties of the implementation resulting from the approach are discussed, and guidelines for future developments are proposed.

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Section: • Telecommand and Telemetry (Tc/tm)mentioning

confidence: 99%

Safety Concept for a Mixed Criticality On-Board Software System ∗

et al. 2015

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“…Table 1 shows that, overall, the runtime implementation needs about 10 (notional) primitives. To date, at least two such kernels have been developed and industrially deployed: the Aonix ObjectAda/Raven technology (Dobbing and Romanski, 1999); and the Technical University of Madrid Open Ravenscar Kernel (ORK) (de la Puente et al, 2000a).…”

Section: Runtime Metricsmentioning

confidence: 99%

“…ORK for ERC32 targets (de la Puente et al, 2000a;ATMEL, 2003), deliberately uses two distinct hardware timers for the two sources of interrupt, because of the difficulty of keeping the drift-less monotonic clock required by the Ravenscar Profile with just one interval timer (Zamorano et al, 2001). …”

Section: Modeling Clock Interruptsmentioning

confidence: 99%

On the Dynamic Semantics and the Timing Behavior of Ravenscar Kernels

2005

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Abstract. Mature research advances in scheduling theory show that carefully-crafted concurrent computational models permit static analysis of real-time behavior. This evidence enables designers to consider using suitable forms of explicit concurrency to model the inherent concurrency of real-time systems. The Ravenscar Profile, a specifically tailored subset of the Ada 95 tasking model, defines a compact and efficient concurrent computational model, especially suited for the development of high integrity, high efficiency real-time systems.Ravenscar runtimes can be implemented by small, efficient, reliable and certifiable kernels. At least two such implementations already exist and are being industrially deployed. The simplicity and intrinsic determinism of Ravenscar kernels facilitate the definition of metrics that cater for very accurate characterization of the dynamic behavior of the runtime and of the execution time of its primitives. Accurate runtime metrics enable forms of response time analysis that minimize the pessimism in the prediction of the runtime influence on the application. This is especially useful for concurrent systems that exhibit significant dependency on runtime support services. This paper recalls the motivations of the Ravenscar Profile, outlines the definition of it and formulates a precise characterisation of the associated runtime metrics.

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“…GNATforLEON is a port to LEON2 targets of GNAT Pro for ERC32 [17]. GNAT Pro for ERC32 and thus GNATforLEON uses a version of the GNAT run-time library (GNARL) specially developed to support the Ravenscar profile on top of a bare board kernel which is an evolved version of the Open Ravenscar Kernel (ORK) [5,7].…”

Section: Introductionmentioning

confidence: 99%