178,717 research outputs found

    A Component Framework for Java-based Real-time Embedded Systems

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    Rank (CORE): A.International audienceThe Real-Time Specification for Java (RTSJ) is becoming a popular choice in the world of real-time and embedded programming. However, RTSJ introduces many non-intuitive rules and restrictions which prevent its wide adoption. Moreover, current state-of-the-art frameworks usually fail to alleviate the development process into higher layers of the software development life-cycle. In this paper we extend our philosophy that RTSJ concepts need to be considered at early stages of software development, postulated in our prior work, in a framework that provides continuum between the design and implementation process. A component model designed specially for RTSJ serves here as a cornerstone. As the first contribution of this work, we propose a development process where RTSJ concepts are manipulated independently from functional aspects. Second, we mitigate complexities of RTSJ-development by automatically generating execution infrastructure where real-time concerns are transparently managed. We thus allow developers to create systems for variously constrained real-time and embedded environments. Performed benchmarks show that the overhead of the framework is minimal in comparison to manually written object-oriented approach, while providing more extensive functionality. Finally, the framework is designed with the stress on dynamic adaptability of target systems, a property we envisage as a fundamental in an upcoming era of massively developed real-time systems

    Review of System Design Frameworks

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    In the last decade, the enormous development of the semiconductor industry with ever-increasing complexities of digital embedded systems and strong market competition with fast time-to-market and low design cost demands have imposed serious difficulty to a conventional design method. Therefore, there emerges a new design flow named model-based system design, which is based on high-level abstraction models, heavy design automation, and extensive component reuse to increase productivity and satisfy the market pressure. This thesis presents reviews of ten high level academic system design frameworks and tools that have been proposed and implemented recently to support the model based design flow, namely System-on-Chip Environment (SCE), Embedded System Environment (ESE), Metropolis, Daedalus, SystemCoDesigner (SCD), xPilot, GAUT, No-Instruction-Set Computer (NISC), Formal System Design (ForSyDe), and Ptolemy II. These tools are then compared to each other in various aspects comprising objective, technique, implementation and capability. Following that, three design flow frameworks, including ESE, Daedalus, and SystemCoDesigner, are experimented for their real usage, performance and practicality. The frameworks and tools implementing the model-based design flow all show promising results. Modelling tools (ForSyDe, and Ptolemy II) can sufficiently capture a wide range of complicated modern systems, while high-level synthesis tools (xPilot, GAUT, and NISC) produce better design qualities in terms of area, power, and cost in comparison to traditional works. Study cases of design flow frameworks (SCE, ESE, Metropolis, Daedalus, and SCD) show the model-based method significantly reduces developing time as well as facilitates the system design process. However, most of these tools and frameworks are being incomplete, and still under the experimental stage. There still be a lot of works needed until the method can be put into practice

    Methods of Technical Prognostics Applicable to Embedded Systems

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    Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy. Dizertační práce přináší přehled základních metod použitelných pro účely predikce zbývající užitné životnosti, jsou zde popsány metriky pomocí, kterých je možné jednotlivé přístupy porovnávat ať už z pohledu přesnosti, ale také i z pohledu výpočetní náročnosti. Jedno z dizertačních jader tvoří doporučení a postup pro výběr vhodné prognostické metody s ohledem na prognostická kritéria. Dalším dizertačním jádrem je představení tzv. částicového filtrovaní (particle filtering) vhodné pro model-based prognostiku s ověřením jejich implementace a porovnáním. Hlavní dizertační jádro reprezentuje případovou studii pro velmi aktuální téma prognostiky Li-Ion baterii s ohledem na trvalé monitorování. Případová studie demonstruje proces prognostiky založené na modelu a srovnává možné přístupy jednak pro odhad doby před vybitím baterie, ale také sleduje možné vlivy na degradaci baterie. Součástí práce je základní ověření modelu Li-Ion baterie a návrh prognostického procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.

    A network-aware framework for energy-efficient data acquisition in wireless sensor networks

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    Wireless sensor networks enable users to monitor the physical world at an extremely high fidelity. In order to collect the data generated by these tiny-scale devices, the data management community has proposed the utilization of declarative data-acquisition frameworks. While these frameworks have facilitated the energy-efficient retrieval of data from the physical environment, they were agnostic of the underlying network topology and also did not support advanced query processing semantics. In this paper we present KSpot+, a distributed network-aware framework that optimizes network efficiency by combining three components: (i) the tree balancing module, which balances the workload of each sensor node by constructing efficient network topologies; (ii) the workload balancing module, which minimizes data reception inefficiencies by synchronizing the sensor network activity intervals; and (iii) the query processing module, which supports advanced query processing semantics. In order to validate the efficiency of our approach, we have developed a prototype implementation of KSpot+ in nesC and JAVA. In our experimental evaluation, we thoroughly assess the performance of KSpot+ using real datasets and show that KSpot+ provides significant energy reductions under a variety of conditions, thus significantly prolonging the longevity of a WSN
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