Supporting timing analysis of vehicular embedded systems through the refinement of timing constraints

Mubeen, Saad; Nolte, Thomas; Sjödin, Mikael; Lundbäck, John; Lundbäck, Kurt-Lennart

doi:10.1007/s10270-017-0579-8

Cited by 35 publications

(19 citation statements)

References 20 publications

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“…by supporting end-to-end timing analysis [14] of software architectures of the system at early stages during the development. Lastly, the automatically generated footprint of the executable image of the system is consistently smaller than for other modelling languages [13]. Whereas our work focuses on RCM, we believe that the evolution problems that we faced are commonly emerging in the transition of similar languages towards the support of multi-core platforms.…”

Section: Contributionmentioning

confidence: 93%

“…Moreover, RCM uses pipe-and-filter 2 communication and distinguishes between the control and data flows among its software components; this communication mechanism resembles the sender receiver communication in the AUTOSAR standard [8]. In [13], we showed how these features contributed to enable early timing verification of the modelled system, e.g. by supporting end-to-end timing analysis [14] of software architectures of the system at early stages during the development.…”

Section: Contributionmentioning

confidence: 99%

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Modelling multi-criticality vehicular software systems: evolution of an industrial component model

et al. 2020

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Software in modern vehicles consists of multi-criticality functions, where a function can be safety-critical with stringent real-time requirements, less critical from the vehicle operation perspective, but still with real-time requirements, or not critical at all. Next-generation autonomous vehicles will require higher computational power to run multi-criticality functions and such a power can only be provided by parallel computing platforms such as multi-core architectures. However, current model-based software development solutions and related modelling languages have not been designed to effectively deal with challenges specific of multi-core, such as core-interdependency and controlled allocation of software to hardware. In this paper, we report on the evolution of the Rubus Component Model for the modelling, analysis, and development of vehicular software systems with multi-criticality for deployment on multi-core platforms. Our goal is to provide a lightweight and technology-preserving transition from model-based software development for single-core to multi-core. This is achieved by evolving the Rubus Component Model to capture explicit concepts for multi-core and parallel hardware and for expressing variable criticality of software functions. The paper illustrates these contributions through an industrial application in the vehicular domain.

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Section: Contributionmentioning

confidence: 93%

Section: Contributionmentioning

confidence: 99%

Modelling multi-criticality vehicular software systems: evolution of an industrial component model

et al. 2020

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“…Especially when it targets the in‐vehicular communication, end‐to‐end analysis must encompass all the system timing properties. Correspondingly, RTA examines imperatively data flows, event processing and timing dependencies [133]. The seminal work of Tindell was the first known formalisation of basic CAN analysis [134].…”

Section: Can Real‐time Analysismentioning

confidence: 99%

Controller area network reliability: overview of design challenges and safety related perspectives of future transportation systems

Lakhal

Nasri

Adouane

et al. 2020

IET intell. transp. syst

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The in‐vehicular networked control system is among the most critical embedded processes. The controller area network (CAN) has prevailed intra‐vehicle communication for decades. Meanwhile, requirements of future transportation systems are expected to emphasise the in‐vehicle communication complexity, which endangers the reliability/safety of the intelligent navigation. At first, this study reviews the recent solutions proposed to overcome the CAN expanding complexity. Challenges that tomorrow's intelligent vehicles may raise for CAN reliability are investigated. The comprehensive coverage of current research efforts to remove the impact of these challenges is presented. Further, the in‐vehicle system reliability of future automated vehicles is also related to the fault diagnosis performances. Hence, different classes of system‐level diagnosis strategies are compared relatively to the requirements of automotive embedded networks. Furthermore, to thoroughly cover CAN reliability engineering issues, focus is given to the automotive validation techniques. The hardware in the loop, real‐time analysis and computer‐aided‐design tools intervene in various phases along the in‐vehicular network life cycle. Parameters that stand behind the efficiency and accuracy of these techniques in validating the new generation of vehicles are analysed. The authors finally draw some deductive predictions about the future directions related to the reliability of the intelligent transportation system in‐vehicular communication.

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“…The respect of timing constraints is crucial for critical real-time embedded systems and must be taken into account at the earliest stages of the design process. End-to-end timing constraints are introduced in many automotive software architectures and modeling languages [46] (e.g., timing model of the AUTOSAR standard [3], timing extensions to EAST-ADL [19], TADL2 language [59]). Computing a single value of data chain latency is not computationally challenging.…”

Section: Introductionmentioning

confidence: 99%

Latency upper bound for data chains of real-time periodic tasks

Kloda

Bertout

Sorel

2020

Journal of Systems Architecture

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The inter-task communication in embedded real-time systems can be achieved using various patterns and be subject to different timing constraints. One of the most basic communication patterns encountered in today's automotive and aerospace software is the data chain. Each task of the chain reads data from the previous task and delivers the results of its computation to the next task. The data passing does not affect the execution of the tasks that are activated periodically at their own rates. As there is no task synchronization, a task does not wait for its predecessor data; it may execute with old data and get new data at its later release. From the design stage of embedded real-time systems, evaluating if data chains meet their timing requirements, such as the latency constraint, is of the highest importance. The trade-off between accuracy and complexity of the timing analysis is a critical element in the optimization process. In this paper, we consider data chains of real-time periodic tasks executed by a fixed-priority preemptive scheduler upon a single processor. We present a method for the worst-case latency calculation of periodic tasks' data chains. As the method has an exponential time complexity, we derive a polynomial-time upper bound. Evaluations carried out on an automotive benchmark demonstrate that the average bound overestimation is less than 10 percent of the actual value.

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Supporting timing analysis of vehicular embedded systems through the refinement of timing constraints

Cited by 35 publications

References 20 publications

Modelling multi-criticality vehicular software systems: evolution of an industrial component model

Modelling multi-criticality vehicular software systems: evolution of an industrial component model

Controller area network reliability: overview of design challenges and safety related perspectives of future transportation systems

Latency upper bound for data chains of real-time periodic tasks

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