On Using the Cloud to Support Online Courses

The increasing interest of online learning is unquestionable nowadays, with MOOCs being taken by thousands of students. However, for online learning to go mainstream it is necessary that professors perceive that the effort required to prepare and manage an online course is manageable. Today, a myriad of inexpensive tools and services can be used to produce and manage online courses with unprecedented ease and without distressing the professor. For that, this paper proposes an architecture based on Cloud services that simplifies the process of managing an online course, from delivering on-demand fully customized remote laboratories to communication automation for student engagement and feedback gathering. This approach has been applied to produce, distribute and manage an Online Course on Cloud Computing with Amazon Web Services. The paper describes the methodology, tools and results of this experience to point out that it is possible to deliver online courses with automatically provisioned labs, with minimal management overhead, while still providing a high quality learning experience to a worldwide audience.Moltó, G.; Caballer Fernández, M. (2014). On Using the Cloud to Support Online Courses. Frontiers in Education Conference. 2014:330-338. doi:10.1109/FIE.2014.7044041S330338201

Gestión de recursos computacionales en el cloud para actividades educativas

En este artículo se describe el uso de la plataforma ODISEA en cuatro asignaturas del Máster Universitario en Computación Paralela y Distribuida (MUCPD) de la Universitat Politècnica de València (UPV). Esta plataforma permite desplegar recursos computacionales sobre proveedores Cloud específicamente configurados para soportar actividades educativas. El instructor declara las necesidades hardware, software y de configuración del entorno de prácticas, que puede ser desplegado automáticamente tanto en un Cloud privado existente en la organización educativa o sobre un Cloud público. Esto permite una flexibilidad sin precedentes en la gestión de recursos de cómputo para actividades educativas. Se resumen las capacidades de ODISEA y el uso en las diferentes asignaturas.SUMMARY -- This paper describes the usage of the ODISEA platform in four subjects of the Master’s Degree in Parallel and Distributed Computing (MUCPD) at the Universitat Politècnica de València (UPV). This platform deploys computational resources on Cloud providers specifically configured to support educational activities. The instructor declares the hardware, software and configuration requirements of the lab resources, which can be automatically deployed both on an on-premise Cloud within the educational center or on a public Cloud. This introduces unprecedented flexibility in the management of computational resources for educational activities. The paper summarizes ODISEA’s features and focuses on the usage experience in the subjects

WINGS: Worflow In Next generation Grids

[ES] WINGS (Workflow In Next Generation Grids) es un sistema workflow independiente de la plataforma diseñado para facilitar la creación de aplicaciones grid. Está compuesto por dos elementos: el lenguaje de definición WINGS y el entorno de ejecución WINGS (WINGS-RT). El primero es un lenguaje XML que utiliza conceptos similares de trabajos anteriores, pero añadiendo nuevos conceptos y evitando la creación de la definición para un entorno o aplicación en concreto. Así, uno de los principales objetivos del lenguaje WINGS es proporcionar la capacidad de ser evolucionado por los usuarios, añadiendo nuevos elementos con nuevas funcionalidades con el fin de adecuarlo a los middlewares actuales y futuros. El sistema de ejecución se encarga de proveer la funcionalidad definida en el lenguaje de definición XML, creando un entorno paralelo para el lanzamiento de los trabajos.[EN] WINGS (Workflow In Next Generation Grids) is a platform-agnostic workflow system designed to make the creation of grid applications easier. It is composed by two elements: the WINGS description language and the WINGS runtime environment (WINGS-RT). The first one is a XML language that uses similar concepts used in previous works, but adding new concepts and avoiding creating the definition for a concrete application or environment. Thus one of the main objectives of the WINGS language is provide the capability of being evolved by the users, adding new elements with new functionality in order to adequate to the current and future middlewares. The runtime system is in charge of providing the functionality defined in the XML description language, creating a parallel environment to launch the jobs.Caballer Fernández, M. (2012). WINGS: Worflow In Next generation Grids. http://hdl.handle.net/10251/19222Archivo delegad

Gestión de infraestructuras virtuales configuradas dinámicamente

En los últimos años y con el auge las tecnologías de virtualización y de las infraestructuras cloud, se abre un nuevo abanico de posibilidades para acceso de recursos de cómputo para el ámbito científico. Estas tecnologías permiten "acceso ubicuo, adaptado y bajo demanda en red a un conjunto compartido de recursos de computación". Estas tecnologías permiten que el acceso a grandes cantidades de recursos virtualizados sea mucho más sencillo para el científico. Si bien la adaptación de aplicaciones a un entorno distribuido sigue requiriendo de una experiencia importante, es posible utilizar de forma eficiente software adaptado a sistemas de colas e incluso computación paralela de memoria distribuida. A pesar de todo, en la actualidad existen diferentes proveedores cloud, diferente software para el despliegue de plataformas cloud, diferentes gestores de máquinas virtuales, y otros componentes que complican el acceso de forma sencilla y homogénea. Por tanto el objetivo principal de esta tesis es la de proporcionar a la comunidad científica el acceso a las tecnologías de virtualización y cloud de manera sencilla. De tal manera que sea muy sencillo el despliegue y gestión de sus infraestructuras virtuales, para que los investigadores solo tengan que centrarse en las tareas propias de su aplicación. Una plataforma Cloud para investigación debe contemplar todos los aspectos necesarios para creación y gestión de las infraestructuras, partiendo de que el investigador debe poder expresar sus requerimientos, tanto hardware como software, sobre los recursos que va a necesitar para la ejecución de su aplicación. En base a los requerimientos definidos por el usuario el sistema debe crear la infraestructura del usuario, teniendo en cuenta aspectos como la selección de despliegues cloud, de imágenes de máquinas virtuales, procesos de contextualización, etc. El sistema también debe permitir que el usuario modifique la cantidad de recursos (elasticidad horizontal) así como las características de los mismos (elasticidad vertical). Por último la plataforma debe proporcionar interfaces tanto a nivel de usuario, mediante aplicaciones de comandos o interfaces gráficas, como a nivel programático para que capas de mayor nivel puedan hacer uso de la funcionalidad mediante un API. La tesis pretende tanto avanzar en las especificaciones y arquitecturas software como desarrollar y testear un prototipo.Caballer Fernández, M. (2014). Gestión de infraestructuras virtuales configuradas dinámicamente [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37376TESISPremios Extraordinarios de tesis doctorale

A framework and a performance assessment for serverless MapReduce on AWS Lambda

[EN] MapReduce is one of the most widely used programming models for analysing large-scale datasets, i.e. Big Data. In recent years, serverless computing and, in particular, Functions as a Service (FaaS) has surged as an execution model in which no explicit management of servers (e.g. virtual machines) is performed by the user. Instead, the Cloud provider dynamically allocates resources to the function invocations and fine-grained billing is introduced depending on the execution time and allocated memory, as exemplified by AWS Lambda. In this article, a high-performant serverless architecture has been created to execute MapReduce jobs on AWS Lambda using Amazon S3 as the storage backend. In addition, a thorough assessment has been carried out to study the suitability of AWS Lambda as a platform for the execution of High Throughput Computing jobs. The results indicate that AWS Lambda provides a convenient computing platform for general-purpose applications that fit within the constraints of the service (15 min of maximum execution time, 3008 MB of RAM and 512 MB of disk space) but it exhibits an inhomogeneous performance behaviour that may jeopardise adoption for tightly coupled computing jobs.This study was supported by the program "Ayudas para la contratacion de personal investigador en formacion de caracter pre-doctoral, programa VALid-d" under grant number ACIF/2018/148 from the Conselleria d'Educacio of the Generalitat Valenciana, Spain. The authors would also like to thank the Spanish "Ministerio de Economia, Industria y Competitividad" for the project "BigCLOE" with reference number TIN2016-79951-R.Giménez-Alventosa, V.; Moltó, G.; Caballer Fernández, M. (2019). A framework and a performance assessment for serverless MapReduce on AWS Lambda. Future Generation Computer Systems. 97:259-274. https://doi.org/10.1016/j.future.2019.02.057S2592749

AVADRA: Análisis Visual Automatizado Dual de Retroalimentación del Alumnado

La obtención de retroalimentación por parte del alumnado acerca de las actividades realizadas en el contexto de una asignatura o curso es fundamental para tenerlas en consideración. Sin embargo, obtener, analizar y visualizar dicha información, para que sea de utilidad al profesor, a menudo requiere el uso de diferentes herramientas provocando que dicha retroalimentación se obvie o, directamente, ni se solicite al alumnado. En esta contribución se describe un recurso docente que permite la recopilación, análisis y visualización agregada de la retrolimentación aportada por el alumnado relativa a la satisfacción y utilidad con la que perciben cada módulo, aplicado a un curso online. Para ello, emplea una estrategia dual. Por un lado, la publicación automática del grado de satisfacción y utilidad agregado indicado por el alumnado en la página web del curso, como mecanismo de atracción de nuevos alumnos. Por otro lado, la actualización de un panel de control web (dashboard) que muestra la información agregada en diferentes escalas temporales para detectar fácilmente problemas en los diferentes módulos. Todo ello, usando servicios gratuitos ofrecidos por Google y a partir de plantillas puestas a disposición con licencia abierta para facilitar la reproducibilidad y adopción por parte de otros docentes.Obtaining feedback from students about the activities carried out in the context of a subject or course is essential to take them into consideration. However, obtaining, analyzing and visualizing said information, to become useful to the teacher, often requires the use of different tools, causing said feedback to be ignored or, directly, not requested from the student. This paper describes a teaching resource that allows the compilation, analysis and aggregated visualization of the feedback provided by the students regarding the satisfaction and usefulness with which they perceive each module, applied to an online course. To do this, it employs a dual strategy. On the one hand, the automatic publication of the aggregated degree of satisfaction and utility indicated by the students on the course website, as a driving mechanism for new students. On the other hand, the update of a web control panel (dashboard) that shows the aggregated information in different time scales to easily detect problems in the different modules. All this, using free services offered by Google and from templates made available with an open license to facilitate reproducibility and adoption by other teachers.Este trabajo ha sido financiado por el Vicerrectorado de Profesorado y Ordenación Académica (VPOA) de la UPV (Convocatoria A+D. Proyectos de Innovación y Mejora Educativa) mediante el proyecto PIME/19-20/166

Vocalizaciones ultrasónicas: Nuevo paradigma para el registro de respuestas emocionales no aprendidas en animales.

Dotzenes Jornades de Foment de la Investigació de la FCHS (Any 2006-2007)El registro de la respuesta emocional en animales posee obvias limitaciones. Los paradigmas utilizados hasta la fecha se basan en el registro de respuestas indirectas en las cuales el componente motor tiene una gran implicación. Así por ejemplo en roedores, en las respuestas de miedo o aversión innata a las alturas o a espacios iluminados y abiertos se emplean laberintos elevados con zonas protegidas o abiertas y se registra el desplazamiento del animal a esos compartimentos controlando que los efectos motores sean mínimos o corrigiendo el efecto. Por esta razón el registro de una respuesta innata no limitada a la conducta motora general del animal resulta de gran relevancia en el estudio de la emoción. En ratas, se ha observado que en condiciones consideradas aversivas se genera un elevado nivel de vocalizaciones de baja frecuencia (20kHz), mientras que en las consideradas apetitivas aumentan las vocalizaciones de alta frecuencia (75kHz). En nuestro estudio, aplicamos estos parámetros a los efectos de una droga ansiolítica como el alcohol y a las vías de administración de la misma. Demostramos que una inyección periférica genera más vocalizaciones aversivas que la administración intracerebral. Así mismo comprobamos que los animales vocalizan menos en el rango de baja frecuencia cuando se les administra alcohol en relación a cuando se les administra el vehículo lo cual apunta a un efecto de reducción de efectos aversivos de esta dosis de alcohol

Una aplicación didáctica para el diseño y simulación de redes de colas

El programa WinNet 3.0 es una herramienta didáctica para el diseño de redes de colas y su simulación. Permite diseñar de una forma sencilla y rápida redes de colas cerradas, abiertas y mixtas; monoclase o multiclase. La red diseñada puede ser analizada mediante simulación. También permite traducir el diseño gráfico al lenguaje de especificación de modelos QNAP2. De esta forma WinNet puede utilizarse como entrada gráfica para QNAP2, el cual implementa múltiples algoritmos de resolución analítica de redes de colas, así como potentes mecanismos de simulación

Serverless computing for container-based architectures

[EN] New architectural patterns (e.g. microservices), the massive adoption of Linux contain- ers (e.g. Docker containers), and improvements in key features of Cloud computing such as auto-scaling, have helped developers to decouple complex and monolithic sys- tems into smaller stateless services. In turn, Cloud providers have introduced serverless computing, where applications can be defined as a workflow of event-triggered functions. However, serverless services, such as AWS Lambda, impose serious restrictions for these applications (e.g. using a predefined set of programming languages or difficulting the installation and deployment of external libraries). This paper addresses such issues by introducing a framework and a methodology to create Serverless Container-aware AR- chitectures (SCAR). The SCAR framework can be used to create highly-parallel event- driven serverless applications that run on customized runtime environments defined as Docker images on top of AWS Lambda. This paper describes the architecture of SCAR together with the cache-based optimizations applied to minimize cost, exemplified on a massive image processing use case. The results show that, by means of SCAR, AWS Lambda becomes a convenient platform for High Throughput Computing, specially for highly-parallel bursty workloads of short stateless jobs.The authors would like to thank the Spanish "Ministerio de Economia, Industria y Competitividad" for the project "BigCLOE" under grant reference TIN2016-79951-R. The authors would also like to thank Jorge Gomes from LIP for the development of the udocker tool.Pérez-González, AM.; Moltó, G.; Caballer Fernández, M.; Calatrava Arroyo, A. (2018). Serverless computing for container-based architectures. Future Generation Computer Systems. 83:50-59. https://doi.org/10.1016/j.future.2018.01.022S50598

Orchestrating Complex Application Architectures in Heterogeneous Clouds

[EN] Private cloud infrastructures are now widely deployed and adopted across technology industries and research institutions. Although cloud computing has emerged as a reality, it is now known that a single cloud provider cannot fully satisfy complex user requirements. This has resulted in a growing interest in developing hybrid cloud solutions that bind together distinct and heterogeneous cloud infrastructures. In this paper we describe the orchestration approach for heterogeneous clouds that has been implemented and used within the INDIGO-DataCloud project. This orchestration model uses existing open-source software like OpenStack and leverages the OASIS Topology and Specification for Cloud Applications (TOSCA) open standard as the modeling language. Our approach uses virtual machines and Docker containers in an homogeneous and transparent way providing consistent application deployment for the users. 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