Polish grid infrastructure for science and research

Structure, functionality, parameters and organization of the computing Grid in Poland is described, mainly from the perspective of high-energy particle physics community, currently its largest consumer and developer. It represents distributed Tier-2 in the worldwide Grid infrastructure. It also provides services and resources for data-intensive applications in other sciences.Comment: Proceeedings of IEEE Eurocon 2007, Warsaw, Poland, 9-12 Sep. 2007, p.44

Collaborative Environment for Grid-based Flood Prediction

This paper presents the design, architecture and main implementation features of the flood prediction application of the Task 1.2 of the EU IST CROSSGRID. The paper begins with the description of the virtual organization of hydrometeorological experts, users, data providers and customers supported by the application. Then the architecture of the application is described, followed by used simulation models and modules of the collaborative environment. The paper ends with vision of future development of the application

Adapting a HEP Application for Running on the Grid

The goal of the EU IST int.eu.grid project is to build middleware facilities which enable the execution of real-time and interactive applications on the Grid. Within this research, relevant support for the HEP application is provided by Virtual Organization, monitoring system, and real-time dispatcher (RTD). These facilities realize the pilot jobs idea that allows to allocate grid resources in advance and to analyze events in real time. In the paper we present HEP Virtual Organization, the details of monitoring, and RTD. We present the way of running the HEP application using the above facilities to fit into the real-time application requirements

CrossBroker: A Grid Metascheduler for Interactive and Parallel Jobs

Execution of parallel and interactive applications on a Grid environment is a challenging problem that requires the cooperation of several middleware tools and services. In this paper, we present our experiences in the development of CrossBroker, a job management service that provides transparent and reliable support for such types of applications. We outline the main components of CrossBroker and how they interact with other middleware services. We also describe specific features of the scheduler used to guarantee resource co-allocation for running MPI jobs remotely over multiple machines spread across several Grid sites or to start interactive applications as fast as possible. These features include a simple time-sharing mechanism that allows fast execution of interactive applications even under heavy occupancy of Grid resources

A classification of emerging and traditional grid systems

The grid has evolved in numerous distinct phases. It started in the early ’90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late ’90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to “glue” different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings. However, third-generation grids’ current architecture doesn’t meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systems’ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area

Active Ontology: An Information Integration Approach for Dynamic Information Sources

In this paper we describe an ontology-based information integration approach that is suitable for highly dynamic distributed information sources, such as those available in Grid systems. The main challenges addressed are: 1) information changes frequently and information requests have to be answered quickly in order to provide up-to-date information; and 2) the most suitable information sources have to be selected from a set of different distributed ones that can provide the information needed. To deal with the first challenge we use an information cache that works with an update-on-demand policy. To deal with the second we add an information source selection step to the usual architecture used for ontology-based information integration. To illustrate our approach, we have developed an information service that aggregates metadata available in hundreds of information services of the EGEE Grid infrastructure

Grid Information Technology as a New Technological Tool for e-Science, Healthcare and Life Science

Nowadays, scientific projects require collaborative environments and powerful computing resources capable of handling huge quantities of data, which gives rise to e-Science. These requirements are evident in the need to optimise time and efforts in activities to do with health. When e-Science focuses on the collaborative handling of all the information generated in clinical medicine and health, e-Health is the result. Scientists are taking increasing interest in an emerging technology – Grid Information Technology – that may offer a solution to their current needs. The current work aims to survey how e-Science is using this technology all around the world. We also argue that the technology may provide an ideal solution for the new challenges facing e-Health and Life Science.Hoy en día, los proyectos científicos requieren poderosos recursos de computación capaces de manejar grandes cantidades de datos, los cuales han dado paso a la ciencia electrónica (e-ciencia). Estos requerimientos se hacen evidentes en la necesidad de optimizar tiempo y esfuerzos en actividades relacionadas con la salud. Cuando la e-ciencia se enfoca en el manejo colaborativo de toda la información generada en la medicina clínica y la salud, da como resultado la salud electrónica (e-salud). Los científicos se han interesado cada vez más y más en una tecnología emergente, como lo es la Tecnología de información en red, la que puede ofrecer solución a sus necesidades cotidianas. El siguiente trabajo apunta a examinar como la e-ciencia es empleada en el mundo. También se discute que la tecnología puede proveer una solución ideal para encarar nuevos desafíos en e-salud y Ciencias de la Vida.Nowadays, scientific projects require collaborative environments and powerful computing resources capable of handling huge quantities of data, which gives rise to e-Science. These requirements are evident in the need to optimise time and efforts in activities to do with health. When e-Science focuses on the collaborative handling of all the information generated in clinical medicine and health, e-Health is the result. Scientists are taking increasing interest in an emerging technology – Grid Information Technology – that may offer a solution to their current needs. The current work aims to survey how e-Science is using this technology all around the world. We also argue that the technology may provide an ideal solution for the new challenges facing e-Health and Life Science

An ActOn-based Semantic Information Service for EGEE

We describe a semantic information service that aggregates metadata from a large number of information sources of a large-scale Grid infrastructure. It uses an ontology-based information integration architecture (ActOn) suitable for the highly dynamic distributed information sources available in Grid systems, where information changes frequently and where the information of distributed sources has to be aggregated in order to solve complex queries. These two challenges are addressed by a Metadata Cache that works with an update-on-demand policy and by an information source selection module that selects the most suitable source at a given point in time. We have evaluated the quality of this information service, and compared it with other similar services from the EGEE production testbed, with promising results

Data Grid tutorials with hands-on experience

Grid technologies are more and more used in scientific as well as in industrial environments but often documentation and the correct usage are either not sufficient or not too well understood. Comprehensive training with hands-on experience helps people first to understand the technology and second to use it in a correct and efficient way. We have organised and run several training sessions in different locations all over the world and provide our experience. The major factors of success are a solid base of theoretical lectures and, more dominantly, a facility that allows for practical Grid exercises during and possibly after tutorial sessions

Interactive Techniques in Grid Computing: A Survey

In Grid computing, the dominating paradigm is batch processing. Grid middleware ships with batch-job support only, while lacking support for interactive applications. The reason is that grid middleware was developed for computation-intensive jobs, which may run for a long time before a result becomes available. This leads to a ``post-mortem'' approach of analysing the output, possibly resulting in a waste of computing and research time. Adding the possibility to observe and steer the job during execution enables the researcher to modify job-parameters without restarting the entire job. In this paper, several interactivity support techniques are explored, followed by several examples proving their usefulness