38 research outputs found

    Towards Grid Interoperability

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    The Grid paradigm promises to provide global access to computing resources, data storage and experimental instruments. It also provides an elegant solution to many resource administration and provisioning problems while offering a platform for collaboration and resource sharing. Although substantial progress has been made towards these goals, nevertheless there is still a lot of work to be done until the Grid can deliver its promises. One of the central issues is the development of standards and Grid interoperability. Job execution is one of the key capabilities in all Grid environments. This is a well understood, mature area with standards and implementations. This paper describes some proof of concept experiments demonstrating the interoperability between various Grid environments

    Semantic Description, Publication and Discovery of Workflows in myGrid

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    The bioinformatics scientific process relies on in silico experiments, which are experiments executed in full in a computational environment. Scientists wish to encode the designs of these experiments as workflows because they provide minimal, declarative descriptions of the designs, overcoming many barriers to the sharing and re-use of these designs between scientists and enable the use of the most appropriate services available at any one time. We anticipate that the number of workflows will increase quickly as more scientists begin to make use of existing workflow construction tools to express their experiment designs. Discovery then becomes an increasingly hard problem, as it becomes more difficult for a scientist to identify the workflows relevant to their particular research goals amongst all those on offer. While many approaches exist for the publishing and discovery of services, there have been few attempts to address where and how authors of experimental designs should advertise the availability of their work or how relevant workflows can be discovered with minimal effort from the user. As the users designing and adapting experiments will not necessarily have a computer science background, we also have to consider how publishing and discovery can be achieved in such a way that they are not required to have detailed technical knowledge of workflow scripting languages. Furthermore, we believe they should be able to make use of others' expert knowledge (the semantics) of the given scientific domain. In this paper, we define the issues related to the semantic description, publishing and discovery of workflows, and demonstrate how the architecture created by the myGrid project aids scientists in this process. We give a walk-through of how users can construct, publish, annotate, discover and enact workflows via the user interfaces of the myGrid architecture; we then describe novel middleware protocols, making use of the Semantic Web technologies RDF and OWL to support workflow publishing and discovery

    Enhancing marine industry risk management through semantic reconciliation of underwater IoT data streams

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    The “Rio+20” United Nations Conference on Sustainable Development (UNCSD) focused on the "Green economy" as the main concept to fight poverty and achieve a sustainable way to feed the planet. For coastal countries, this concept translates into "Blue economy", the sustainable exploitation of marine environments to fulfill humanity needs for resources, energy, and food. This puts a stress on marine industries to better articulate their processes to gain and share knowledge of different marine habitats, and to reevaluate the data value chains established in the past and to support a data fueled market that is going only to in the near future.The EXPOSURES project is working in conjunction with the SUNRISE project to establish a new marine information ecosystem and demonstrate how the ‘Internet of Things’ (IoT) can be exploited for marine applications. In particular EXPOSURES engaged with the community of stakeholders in order to identify a new data value chain which includes IoT data providers, data analysts, and harbor authorities. Moreover we integrated the key technological assets that couple OGC standards for raster data management and manipulation and semantic technologies to better manage data assets.This paper presents the identified data value chain along with the use cases for validating it, and the system developed to semantically reconcile and manage such data collections

    The OMII Software Distribution

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    This paper describes the work carried out at the Open Middleware Infrastructure Institute (OMII) and the key elements of the OMII software distribution that have been developed in collaboration with members of the Managed Programme Initiative. The main objective of the OMII is to preserve and consolidate the achievements of the UK e-Science Programme by collecting, maintaining and improving the software modules that form the key components of a generic Grid middleware. Recently, the activity at Southampton has been extended beyond 2009 through a new project, OMII-UK, that forms a partnership that now includes the OGSA-DAI activities at Edinburgh and the myGrid project at Manchester

    Principles of personalisation of service discovery

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    We define personalisation as the set of capabilities that enables a user or an organisation to customise their working environment to suit their specific needs, preferences and circumstances. In the context of service discovery on the Grid, the demand for personalisation comes from individual users, who want their preferences to be taken into account during the search and selection of suitable services. These preferences can express, for example, the reliability of a service, quality of results, functionality, and so on. In this paper, we identify the problems related to personalising service discovery and present our solution: a personalised service registry or View. We describe scenarios in which personalised service discovery would be useful and describe how our technology achieves them

    Performance Engineering, PSEs and the GRID

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    Performance Engineering is concerned with the reliable prediction and estimation of the performance of scientific and engineering applications on a variety of parallel and distributed hardware. This paper reviews the present state of the art in 'Performance Engineering' for both parallel computing and meta-computing environments and attempts to look forward to the application of these techniques in the wider context of Problem Solving Environments and the Grid. The paper compares various techniques such as benchmarking, performance measurements, analytical modelling and simulation, and highlights the lessons learned in the related projects. The paper concludes with a discussion of the challenges of extending such methodologies to computational Grid environments

    Experiences using the UML profile for MARTE to stochastically model postproduction interactive applications

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    Abstract: We describe a practical approach applying the UML 2.0 standard MARTE profile to model stochastic interactive application workflows, using the PapyrusUML editor. We use the PaStep, PaCommStep, PaLogicalResource and GaCommHost MARTE stereotypes and find them sufficient for stochastic modelling with the exception of being unable to define non-standard probability distributions. We have investigated both Markovian stochastic models and discrete event simulation models, serializing UML deployment and state machine diagrams to automate model creation. The choice between using a stochastic model (e.g. PRISM Markov models) or discrete event simulation model (e.g. Monte Carlo simulations) depends on the complexity of the model, accuracy required and compute time needed. We find that PRISM models are fast to execute if the complexity is small and produce numerically accurate results. Discrete event simulation models are slower to execute but scale much better and are probably the default solution to a model of unknown complexity

    HUMANE Wikipedia simulation modelling bootstrapping data

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    This data set has been derived from the Simple English Wikipedia data publicly available and post-processed in the WikiWarMonitor project. The data set this is derived from is available from: http://wwm.phy.bme.hu/light.html The data set comprises a collection of 15 CSV files with summary statistics of the contributors to Wikipedia (Simple English only) in the period of 18/05/2001 to 17/10/2012. The files cover: Statistics of registered users, anonymous users and bots. History of revert activity History of edit wars Activity statistics broken down into weekly snapshots Each CSV file has a descriptive header that is generally self-explanatory, so the data is not further described here. However, note that in the activity_snapshots_aggregated.csv file, the edit war conditions are as follows: Condition 1: ongoing (started before the snapshot and continues) Condition 2: started and finished within the snapshot Condition 3: started within the snapshot, but did not finish yet Condition 4: started before the snapshot, but finished within the snapshot </span

    Automating Experiments Using Semantic Data on a Bioinformatics Grid

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    myGrid assists bioinformaticians in designing and executing in silico experiments using the Grid’s resources. In myGrid, much of this experimental design has been encoded as workflows. Workflows must be represented at tiered levels of detail to ensure that they can respond to changes in service availability, be customized to services in different locations, and be shared with others to varying degrees. The authors have developed workflow templates in which classes of services are composed, and a resolution mechanism by which these classes are instantiated. The specification of service classes and their resolution depends on seven kinds of service metadata. Functionally equivalent services vary widely in implementation. The authors describe workflow harmonization in which the workflow is modified to accommodate variations between substituted services. Finally, they examine the role of scientist and automated process in resolution and harmonization and discuss scope for further automation
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