Network-aware heuristics for inter-domain meta-scheduling in Grids

AbstractGrid computing generally involves the aggregation of geographically distributed resources in the context of a particular application. As such resources can exist within different administrative domains, requirements on the communication network must also be taken into account when performing meta-scheduling, migration or monitoring of jobs. Similarly, coordinating efficient interaction between different domains should also be considered when performing such meta-scheduling of jobs. A strategy to perform peer-to-peer-inspired meta-scheduling in Grids is presented. This strategy has three main goals: (1) it takes the network characteristics into account when performing meta-scheduling; (2) communication and query referral between domains is considered, so that efficient meta-scheduling can be performed; and (3) the strategy demonstrates scalability, making it suitable for many scientific applications that require resources on a large scale. Simulation results are presented that demonstrate the usefulness of this approach, and it is compared with other proposals from literature

Integration of Multiple Data Sources for predicting the Engagement of Students in Practical Activities

This work presents the integration of an automatic assessment system for virtual/remote laboratories and the institutional Learning Management System (LMS), in order to analyze the students’ progress and their collaborative learning in virtual/remote laboratories. As a result of this integration, it is feasible to extract useful information for the characterization of the students’ learning process and detecting the students’ engagement with the practical activities of our subjects. From this integration, a dashboard has been created to graphically present to lecturers the analyzed results. Thanks to this, faculty can use the analyzed information in order to guide the learning/teaching process of each student. As an example, a subject focused on the configuration of network services has been chosen to implement our proposal

Hispanic Medieval Tagger (HisMeTag): una aplicación web para el etiquetado de entidades en textos medievales

El resumen presenta la herramienta de etiquetado de entidades nombradas en textos medievales en español. Este trabajo se enmarca dentro de los proyectos de investigación, proyecto europeo ERC-2015-STG-679528 POSTDATA

EVI-LINHD, un Entorno Virtual de Investigación para la edición digital académica.

EVI-LINHD, un Entorno Virtual de Investigación para la edición digital académica

Proposals for enhancing the provision of quality of service in grids.

Propuestas para la Mejora de la Calidad de Servicio en Sistemas Grid La computación Grid permite la agregación de recursos heterogéneos, geográficamente distribuidos, para ejecutar aplicaciones paralelas y distribuidas de gran escala, en ciencia, ingeniería y comercio. Los sistemas Grid actuales son entornos altamente variables, hechos de una serie de organizaciones independientes que comparten sus recursos para crear lo que se conoce como Organización Virtual (Virtual Organizations -- VOs). Esta variabilidad hace que la calidad de servicio (Quality of Service -- QoS) sea altamente deseable, aunque es a menudo muy difícil de conseguir en la práctica. Una razón para esta limitación es la falta de control sobre la red que interconecta los componentes de un sistema Grid. Alcanzar QoS extremo-a-extremo es a menudo difícil, sin embargo, para aplicaciones que necesitan una respuesta inmediata (como por ejemplo, visualización colaborativa), el Grid debe proporcionar a los usuarios algún tipo de seguridad sobre el uso de recursos -- un aspecto no trivial cuando se piensa en el contexto de la QoS de red.En una VO, las entidades se comunican entre ellas usando una red de interconexión, lo que resulta en que la red juega un papel esencial en los sistemas Grid. Esta Tesis investiga la provision de QoS por medio de la selección eficiente del recurso computacional donde se ejecutará cada trabajo (lo que se conoce como meta-planificación), que considera a la red como un parámetro clave. Se propone una arquitectura de meta-planificación para Grid, que se centra en el intercambio de ficheros de entrada/ salida entre usuarios y recursos de computación y en el impacto que tienen estos intercambios sobre las prestaciones que reciben los usuarios. Se han desarrollado propuestas para la meta-planificación dentro de un dominio administrativo, así como entre dominios. Estos estudios se han desarrollado mediante el simulador GridSim, una herramienta de simulación de eventos discretos, con el fin de que los distintos experimentos pudieran repetirse y evaluarse más fácilmente. Más específicamente, esta Tesis presenta las siguientes contribuciones: Esta Tesis presenta una arquitectura para la provisión de QoS en Grids, que incluye meta-planificación eficiente y control de admisión de conexiones. Esto se hace dentro de un dominio administrativo (meta\-planificación intra-dominio), y entre dominios (meta-planificación inter-dominio). Esta Tesis sugiere la utilización de ideas de computación autonómica para realizar la meta-planificación eficiente de trabajos a recursos en el escenario intra-dominio. Esta Tesis sugiere el uso de ideas peer-to-peer con el fin de realizar la meta-planificación eficientemente en el escenario inter-dominio

An autonomic network-aware scheduling architecture for grid computing

Grid technologies have enabled the aggregation of geographically distributed resources, in the context of a particular application. The network remains an important requirement for any Grid application, as entities involved in a Grid system (such as users, services, and data) need to communicate with each other over a network. The performance of the network must therefore be considered when carrying out tasks such as scheduling, migration or monitoring of jobs. Surprisingly, many existing QoS efforts ignore the network and focus instead on processor workload and disk access. Making use of the network in an efficient and fault tolerance manner, in the context of such existing research, leads to a significant number of research challenges. One way to address these problems is to make Grid middleware incorporate the concept of autonomic systems. Such a change would involve the development of "self-configuring" systems that are able to make decisions autonomously, and adapt themselves as the system status changes. We propose an autonomic network-aware scheduling infrastructure that is capable of adapting its behavior to the current status of the environment

Extending GridSim with an Architecture for Failure Detection

Grid technologies are emerging as the next generation of distributed computing, allowing the aggregation of resources that are geographically distributed across different locations. However, these resources are independent and managed separately by various organizations with different policies. This will have a major impact to users who submit their jobs to the Grid, as they have to deal with issues such as policy heterogeneity, security and fault tolerance. Moreover, the changes of Grid conditions, such as resources that may become unavailable for a period of time due to maintenance and/or suffer failures, would significantly affect the Quality of Service (QoS) requirements of users. Therefore, it is essential for users to take into account the effects of resource failures during jobs execution. In this paper, we present our work on introducing resource failures and failure detection into the GridSim simulation toolkit. As we need to conduct repeatable and controlled experiments, it is easier to use simulation as a means of studying complex scenarios. We also give a detailed description of the overall design and a use case scenario demonstrating the conditions of resources varied over time.

A GridWay-based autonomic network-aware metascheduler

One of the key motivations of computational and data grids is the ability to make coordinated use of heterogeneous computing resources which are geographically dispersed. Consequently, the performance of the network linking all the resources present in a grid has a significant impact on the performance of an application. It is therefore essential to consider network characteristics when carrying out tasks such as scheduling, migration or monitoring of jobs. This work focuses on an implementation of an autonomic network-aware meta-scheduling architecture that is capable of adapting its behavior to the current status of the environment, so that jobs can be efficiently mapped to computing resources. The implementation extends the widely used GridWay meta-scheduler and relies on exponential smoothing to predict the execution and transfer times of jobs. An autonomic control loop (which takes account of CPU use and network capability) is used to alter job admission and resource selection criteria to improve overall job completion times and throughput. The implementation has been tested using a real testbed involving heterogeneous computing resources distributed across different national organizations