13,145 research outputs found

    A New Approach to Memory Partitioning in On-board Spacecraft Software. In Fabrice Kordon and Tullio Vardanega (eds.), Reliable Software Technologies

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    The current trend to use partitioned architectures in on-board spacecraft software requires applications running on the same computer platform to be isolated from each other both in the temporal and memory domains. Memory isolation techniques currently used in Integrated Modular Avionics for Aeronautics usually require a Memory Management Unit (MMU), which is not commonly available in the kind of processors currently used in the Space domain. Two alternative approaches are discussed in the paper, based on some features of Ada and state-of-the art compilation tool-chains. Both approaches provide safe memory partitioning with less overhead than current IMA techniques. Some footprint and performance metrics taken on a prototype implementation of the most flexible approach are included

    Open Source Platforms for Big Data Analytics

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    O conceito de Big Data tem tido um grande impacto no campo da tecnologia, em particular na gestão e análise de enormes volumes de informação. Atualmente, as organizações consideram o Big Data como uma oportunidade para gerir e explorar os seus dados o máximo possível, com o objetivo de apoiar as suas decisões dentro das diferentes áreas operacionais. Assim, é necessário analisar vários conceitos sobre o Big Data e o Big Data Analytics, incluindo definições, características, vantagens e desafios. As ferramentas de Business Intelligence (BI), juntamente com a geração de conhecimento, são conceitos fundamentais para o processo de tomada de decisão e transformação da informação. Ao investigar as plataformas de Big Data, as práticas industriais atuais e as tendências relacionadas com o mundo da investigação, é possível entender o impacto do Big Data Analytics nas pequenas organizações. Este trabalho pretende propor soluções para as micro, pequenas ou médias empresas (PME) que têm um grande impacto na economia portuguesa, dado que representam a maioria do tecido empresarial. As plataformas de código aberto para o Big Data Analytics oferecem uma grande oportunidade de inovação nas PMEs. Este trabalho de pesquisa apresenta uma análise comparativa das funcionalidades e características das plataformas e os passos a serem tomados para uma análise mais profunda e comparativa. Após a análise comparativa, apresentamos uma avaliação e seleção de plataformas Big Data Analytics (BDA) usando e adaptando a metodologia QSOS (Qualification and Selection of software Open Source) para qualificação e seleção de software open-source. O resultado desta avaliação e seleção traduziu-se na eleição de duas plataformas para os testes experimentais. Nas plataformas de software livre de BDA foi usado o mesmo conjunto de dados assim como a mesma configuração de hardware e software. Na comparação das duas plataformas, demonstrou que a HPCC Systems Platform é mais eficiente e confiável que a Hortonworks Data Platform. Em particular, as PME portuguesas devem considerar as plataformas BDA como uma oportunidade de obter vantagem competitiva e melhorar os seus processos e, consequentemente, definir uma estratégia de TI e de negócio. Por fim, este é um trabalho sobre Big Data, que se espera que sirva como um convite e motivação para novos trabalhos de investigação.The concept of Big Data has been having a great impact in the field of technology, particularly in the management and analysis of huge volumes of information. Nowadays organizations look for Big Data as an opportunity to manage and explore their data the maximum they can, with the objective of support decisions within its different operational areas. Thus, it is necessary to analyse several concepts about Big Data and Big Data Analytics, including definitions, features, advantages and disadvantages. Business intelligence along with the generation of knowledge are fundamental concepts for the process of decision-making and transformation of information. By investigate today's big data platforms, current industrial practices and related trends in the research world, it is possible to understand the impact of Big Data Analytics on small organizations. This research intends to propose solutions for micro, small or médium enterprises (SMEs) that have a great impact on the Portuguese economy since they represente approximately 90% of the companies in Portugal. The open source platforms for Big Data Analytics offers a great opportunity for SMEs. This research work presents a comparative analysis of those platforms features and functionalities and the steps that will be taken for a more profound and comparative analysis. After the comparative analysis, we present an evaluation and selection of Big Data Analytics (BDA) platforms using and adapting the Qualification and Selection of software Open Source (QSOS) method. The result of this evaluation and selection was the selection of two platforms for the empirical experiment and tests. The same testbed and dataset was used in the two Open Source Big Data Analytics platforms. When comparing two BDA platforms, HPCC Systems Platform is found to be more efficient and reliable than Hortonworks Data Platform. In particular, Portuguese SMEs should consider for BDA platforms an opportunity to obtain competitive advantage and improve their processes and consequently define an IT and business strategy. Finally, this is a research work on Big Data; it is hoped that this will serve as an invitation and motivation for new research

    Big Data and the Internet of Things

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    Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea
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