2,443 research outputs found

    Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

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    The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209

    On the stability of θ\theta-methods for DDEs and PDDEs

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    In this paper, the stability of θ\theta-methods for delay differential equations is studied based on the test equation y(t)=Ay(t)+By(tτ)y'(t)=-A y(t) + B y(t-\tau), where τ\tau is a constant delay and AA is a positive definite matrix. It is mainly considered the case where the matrices AA and BB are not simultaneosly diagonalizable and the concept of field of values is used to prove a sufficient condition for unconditional stability of these methods and another condition which also guarantees their stability, but according to the step size. The results obtained are also simplified for the case where the matrices AA and BB are simultaneously diagonalizable and compared with other similar works for the general case. Several numerical examples in which the theory discussed here is applied to parabolic problems given by partial delay differential equations with a diffusion term and a delayed term are presented, too.Comment: 17 pages, 21st IMACS World Congres

    ICT and functional diversity: knowledge of the teaching staff

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    La educación de calidad en igualdad y equidad requiere el compromiso de todos los miembros de la comunidad educativa. Este se adquiere favoreciendo la formación permanente del profesorado, un aprendizaje continuo adaptado a las necesidades y a las características de los alumnos. En este contexto, el presente artículo muestra los resultados de una investigación cuyo propósito ha sido conocer el nivel de formación y conocimiento del profesorado de educación primaria de Andalucía, con respecto a la aplicación de las TIC a personas con diversidad funcional. El diseño de investigación utilizado ha sido de tipo mixto (metodología cuantitativa y cualitativa), analizándose 342 cuestionarios suministrados a docentes de educación primaria y 84 entrevistas realizadas a informantes claves (miembros de equipos directivos, coordinadores TIC, directores y asesores tecnológicos de centros de formación del profesorado). Entre las conclusiones podemos destacar la falta de conciencia y preparación por parte del profesorado, así como que el desarrollo de experiencias de formación en este ámbito sigue siendo insuficiente y, en ocasiones, inexistente.Quality education in equality and equity requires the commitment of all members of the educational community. This is acquired by promoting the ongoing training of teachers, a continuous learning adapted to the needs and characteristics of the students. In this context, this article shows the results of a research whose purpose has been to know the level of training and knowledge of teachers of primary education in Andalusia, regarding the application of ICT to people with functional diversity. The research design used has been of mixed type (quantitative and qualitative methodology), analyzing 342 questionnaires provided to teachers of primary education and 84 interviews with key informants (members of management teams, ICT coordinators, directors and technological advisers of training centers of teachers). Among the conclusions we can highlight the lack of awareness and preparation on the part of the teaching staff, as well as the development of training experiences in this area is still insufficient and, sometimes, non-existent

    Using FPGA for visuo-motor control with a silicon retina and a humanoid robot

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    The address-event representation (AER) is a neuromorphic communication protocol for transferring asynchronous events between VLSI chips. The event information is transferred using a high speed digital parallel bus. This paper present an experiment based on AER for visual sensing, processing and finally actuating a robot. The AER output of a silicon retina is processed by an AER filter implemented into a FPGA to produce a mimicking behaviour in a humanoid robot (The RoboSapiens V2). We have implemented the visual filter into the Spartan II FPGA of the USB-AER platform and the Central Pattern Generator (CPG) into the Spartan 3 FPGA of the AER-Robot platform, both developed by authors.Unión Europea IST-2001-34124 (CAVIAR)Ministerio de Ciencia y Tecnología TIC-2003-08164-C03-0

    Responsabilidad social: perspectiva del alumnado de Administración y Dirección de Empresas

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    [Resumen] En esta comunicación se recoge la perspectiva del alumnado perteneciente a primero del grado de Administración y Dirección de Empresas de la Facultad de Economía y Empresa, en la Universidade da Coruña durante el curso 2016-2017, en torno a la responsabilidad social. Este trabajo está dividido en tres fases, la primera, la recogida de información cuantitativa mediante un cuestionario estructurado, la segunda, el desarrollo de un trabajo cualitativo por parte del alumnado y la última fase, exposición y reflexión oral del alumnado en torno a la temática. En la primera fase de este trabajo se analiza el grado de conocimiento del concepto de la responsabilidad social; la identificación de las dimensiones de la responsabilidad social; la principal finalidad que percibe el alumnado para llevar a cabo políticas de responsabilidad social en las organizaciones; la clasificación de los sectores según su grado de implicación en materia de responsabilidad social (entre los que se encuadra la educación en comparación con otros sectores); la importancia de los requisitos para clasificar a las organizaciones como socialmente responsables; y los programas en los que desearía participar el alumnado una vez que finalicen sus estudios en la universidad

    DISCERNER: Dynamic selection of resource manager in hyper-scale cloud-computing data centres

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    Data centres constitute the engine of the Internet, and run a major portion of large web and mobile applications, content delivery and sharing platforms, and Cloud-computing business models. The high performance of such infrastructures is therefore critical for their correct functioning. This work focuses on the improvement of data-centre performance by dynamically switching the main data-centre governance software system: the resource manager. Instead of focusing on the development of new resource-managing models as soon as new workloads and patterns appear, we propose DISCERNER, a decision-theory model that can learn from numerous data-centre execution logs to determine which existing resource-managing model may optimise the overall performance for a given time period. Such a decision-theory system employs a classic machine-learning classifier to make real-time decisions based on past execution logs and on the current data-centre operational situation. A set of extensive and industry-guided experiments has been simulated by a validated data-centre simulation tool. The results obtained show that the values of key performance indicators may be improved by at least 20% in realistic scenarios.Ministerio de Ciencia e Innovación RTI2018-098062-A-I0
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