1,737 research outputs found

    MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

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    An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour

    Autonomic Management Policy SpeciïŹcation: from UML to DSML

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    International audienceAutonomic computing is recognized as one of the most promizing solutions to address the increasingly complex task of distributed environments' administration. In this context, many projects relied on software components and architectures to provide autonomic management frameworks. We designed such a component-based autonomic management framework, but observed that the interfaces of a component model are too low-level and difficult to use. Therefore, we introduced UML diagrams for the modeling of deployment and management policies. However, we had to adapt/twist the UML semantics in order to meet our requirements, which led us to define DSMLs. In this paper, we present our experience in designing the Tune system and its support for management policy specification, relying on UML diagrams and on DSMLs. We analyse these two approaches, pinpointing the benefits of DSMLs over UML

    Preface of the Proceedings of WRAP 2004

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    A Smart Decision System for Digital Farming

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    [EN] New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.This paper has been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR and by the "Ministerio de Ciencia, Innovacion y Universidades" through the "Ayudas para la adquisicion de equipamiento cientifico-tecnico, Subprograma estatal de infraestructuras de investigacion y equipamiento cientifico-tecnico (plan Estatal i+d+i 2017-2020)" (project EQC2018-004988-P).Cambra-Baseca, C.; Sendra, S.; Lloret, J.; TomĂĄs GironĂ©s, J. (2019). A Smart Decision System for Digital Farming. Agronomy. 9(5):1-19. https://doi.org/10.3390/agronomy9050216S11995Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787-2805. doi:10.1016/j.comnet.2010.05.010Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171-209. doi:10.1007/s11036-013-0489-0De Mauro, A., Greco, M., & Grimaldi, M. (2016). A formal definition of Big Data based on its essential features. Library Review, 65(3), 122-135. doi:10.1108/lr-06-2015-0061Haghverdi, A., Leib, B. G., Washington-Allen, R. A., Ayers, P. D., & Buschermohle, M. J. (2015). Perspectives on delineating management zones for variable rate irrigation. Computers and Electronics in Agriculture, 117, 154-167. doi:10.1016/j.compag.2015.06.019Vazquez, J. I., Ruiz-de-Garibay, J., Eguiluz, X., Doamo, I., Renteria, S., & Ayerbe, A. (2010). Communication architectures and experiences for web-connected physical Smart objects. 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). doi:10.1109/percomw.2010.5470521Misra, S., Barthwal, R., & Obaidat, M. S. (2012). Community detection in an integrated Internet of Things and social network architecture. 2012 IEEE Global Communications Conference (GLOBECOM). doi:10.1109/glocom.2012.6503350Atzori, L., Iera, A., & Morabito, G. (2014). From «smart objects» to «social objects»: The next evolutionary step of the internet of things. IEEE Communications Magazine, 52(1), 97-105. doi:10.1109/mcom.2014.6710070Agrivi App http://www.agrivi.com/en/reApollo Project http://apollo-h2020.eu/Cambra, C., Sendra, S., Lloret, J., & Lacuesta, R. (2018). Smart System for Bicarbonate Control in Irrigation for Hydroponic Precision Farming. Sensors, 18(5), 1333. doi:10.3390/s18051333Ortiz, A. M., Hussein, D., Park, S., Han, S. N., & Crespi, N. (2014). The Cluster Between Internet of Things and Social Networks: Review and Research Challenges. IEEE Internet of Things Journal, 1(3), 206-215. doi:10.1109/jiot.2014.2318835Ji, Z., Ganchev, I., O’Droma, M., Zhao, L., & Zhang, X. (2014). A Cloud-Based Car Parking Middleware for IoT-Based Smart Cities: Design and Implementation. Sensors, 14(12), 22372-22393. doi:10.3390/s141222372Ning, H., & Wang, Z. (2011). Future Internet of Things Architecture: Like Mankind Neural System or Social Organization Framework? IEEE Communications Letters, 15(4), 461-463. doi:10.1109/lcomm.2011.022411.11012

    Emerging research directions in computer science : contributions from the young informatics faculty in Karlsruhe

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    In order to build better human-friendly human-computer interfaces, such interfaces need to be enabled with capabilities to perceive the user, his location, identity, activities and in particular his interaction with others and the machine. Only with these perception capabilities can smart systems ( for example human-friendly robots or smart environments) become posssible. In my research I\u27m thus focusing on the development of novel techniques for the visual perception of humans and their activities, in order to facilitate perceptive multimodal interfaces, humanoid robots and smart environments. My work includes research on person tracking, person identication, recognition of pointing gestures, estimation of head orientation and focus of attention, as well as audio-visual scene and activity analysis. Application areas are humanfriendly humanoid robots, smart environments, content-based image and video analysis, as well as safety- and security-related applications. This article gives a brief overview of my ongoing research activities in these areas

    A TYPOLOGY OF TECHNOLOGICAL ENABLERS OF WEBSITE SERVICE FAILURE PREVENTION

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    An increasing range of services are now offered via online applications and e-commerce websites. However, problems with online services still occur at times, even for the best service providers due to the technical failures, informational failures, or lack of required website functionalities. Also, the widespread and increasing implementation of web services means that service failures are both more likely to occur, and more likely to have serious consequences. In this paper we first develop a digital service value chain framework based on existing service delivery models adapted for digital services. We then review current literature on service failure prevention, and provide a typology of technolo- gies and approaches that can be used to prevent failures of different types (functional, informational, system), that can occur at different stages in the web service delivery. This makes a contribution to theory by relating specific technologies and technological approaches to the point in the value chain framework where they will have the maximum impact. Our typology can also be used to guide the planning, justification and design of robust, reliable web services
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