187,043 research outputs found

    Provenance-based trust for grid computing: Position Paper

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    Current evolutions of Internet technology such as Web Services, ebXML, peer-to-peer and Grid computing all point to the development of large-scale open networks of diverse computing systems interacting with one another to perform tasks. Grid systems (and Web Services) are exemplary in this respect and are perhaps some of the first large-scale open computing systems to see widespread use - making them an important testing ground for problems in trust management which are likely to arise. From this perspective, today's grid architectures suffer from limitations, such as lack of a mechanism to trace results and lack of infrastructure to build up trust networks. These are important concerns in open grids, in which "community resources" are owned and managed by multiple stakeholders, and are dynamically organised in virtual organisations. Provenance enables users to trace how a particular result has been arrived at by identifying the individual services and the aggregation of services that produced such a particular output. Against this background, we present a research agenda to design, conceive and implement an industrial-strength open provenance architecture for grid systems. We motivate its use with three complex grid applications, namely aerospace engineering, organ transplant management and bioinformatics. Industrial-strength provenance support includes a scalable and secure architecture, an open proposal for standardising the protocols and data structures, a set of tools for configuring and using the provenance architecture, an open source reference implementation, and a deployment and validation in industrial context. The provision of such facilities will enrich grid capabilities by including new functionalities required for solving complex problems such as provenance data to provide complete audit trails of process execution and third-party analysis and auditing. As a result, we anticipate that a larger uptake of grid technology is likely to occur, since unprecedented possibilities will be offered to users and will give them a competitive edge

    Experiences with deploying legacy code applications as grid services using GEMLCA

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    One of the biggest obstacles in the wide-spread industrial take-up of Grid technology is the existence of a large amount of legacy code programs that is not accessible as Grid Services. On top of that, Grid technology challenges the user in order to intuitively interconnect and utilize resources in a friendly environment. This paper describes how legacy code applications were transformed into Grid Services using GEMLCA providing a user-friendly high-level Grid environment for deployment, and running them through the P-GRADE Grid portal. GEMLCA enables the use of legacy code programs as Grid services without modifying the original code. Using the P-GRADE Grid portal with GEMLCA it is possible to deploy legacy code applications as Grid services and use them in the creation and execution of complex workflows. This environment is tested by deploying and executing several legacy code applications on different sites of the UK e-Science OGSA testbed. © Springer-Verlag Berlin Heidelberg 2005

    A posteriori study of filtered Euler-Euler two-phase model using a high resolution simulation of a 3D periodic circulating fluidized bed

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    Gas-particle flows in vertical risers are involved in many industrial scale fluidized bed applications such as catalytic cracking, fossil or biomass combustion. Risers flows are often simulated by two-fluid model equations coupled with closures developed in the frame the kinetic theory of granular media. However, two-fluid model discretized over coarse mesh with respect to particle clustering size are performed for large units because of limited computational resources. Now, it is well established that meso-scales cancelled out by coarse mesh simulations have dramatic effect on overall behaviour of flows. This study proposed a sub-grid modeling approach for effective drag force and particle stresses which accounts for the effects of unresolved structures on the resolved flows

    Intelligent Decision Support System for Energy Management in Demand Response Programs and Residential and Industrial Sectors of the Smart Grid

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    This PhD thesis addresses the complexity of the energy efficiency control problem in residential and industrial customers of Smart electrical Grid, and examines the main factors that affect energy demand, and proposes an intelligent decision support system for applications of demand response. A multi criteria decision making algorithm is combined with a combinatorial optimization technique to assist energy managers to decide whether to participate in demand response programs or obtain energy from distributed energy resources

    Direct Use of Low Enthalpy Deep Geothermal Resources in the East African Rift Valley

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    Geothermal energy is already harnessed across East Africa to provide hundreds of megawatts of electricity, with significant plans for future expansion towards generation at the gigawatt scale. This power generation utilizes the high steam temperatures (typically more than 200 °C) that are available in several locations in Kenya, Ethiopia and elsewhere. The presence of these high enthalpy resources has deflected attention from the often attractive low and medium enthalpy resources present across a more extensive portion of the region. Geothermally heated water at cooler temperatures (less than 90 °C) could be widely produced by drilling shallower and cheaper boreholes than those required for power production. This low enthalpy resource could be widely exploitable throughout the Rift Valley, offering a low carbon, sustainable, reliable and commercially competitive source of heating, drying and cooling (via absorption chillers) to local farmers and growers, and for low temperature commercial and industrial uses. Applications of this type would displace expensive fossil fuels, reducing costs and carbon emissions as well as improving the region’s energy and food security. The power input for pump systems can be accommodated by relatively small generators, so direct heat projects could be beneficial to consumers in areas with no grid access

    Integrating formal reasoning into component-based approach to reconfigurable distributed systems

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    Distributed computing is becoming ubiquitous in recent years in many areas, especially the scientific and industrial ones, where the processing power - even that of supercomputers - never seems to be enough. Grid systems were born out of necessity, and had to grow quickly to meet requirements which evolved over time, becoming today’s complex systems. Even the simplest distributed system nowadays is expected to have some basic functionalities, such as resources and execution management, security and optimization features, data control, etc. The complexity of Grid applications is also accentuated by their distributed nature, making them some of the most elaborate systems to date. It is often too easy that these intricate systems happen to fall in some kind of failure, it being a software bug, or plain simple human error; and if such a failure occurs, it is not always the case that the system can recover from it, possibly meaning hours of wasted computational power. In this thesis, some of the problems which are at the core of the development and mainte- nance of Grid software applications are addressed by introducing novel and solid approaches to their solution. The difficulty of Grid systems to deal with unforeseen and unexpected cir- cumstances resulting from dynamic reconfiguration can be identified. Such problems are often related to the fact that Grid applications are large, distributed and prone to resource failures. This research has produced a methodology for the solution of this problem by analysing the structure of distributed systems and their reliance on the environment which they sit upon, often overlooked when dealing with these types of scenarios. It is concluded that the way that Grid applications interact with the infrastructure is not sufficiently addressed and a novel approach is developed in which formal verification methods are integrated with distributed applications development and deployment in a way that includes the environment. This approach allows for reconfiguration scenarios in distributed applications to proceed in a safe and controlled way, as demonstrated by the development of a prototype application

    A Distributed Computing Architecture for the Large-Scale Integration of Renewable Energy and Distributed Resources in Smart Grids

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    We present a distributed computing architecture for smart grid management, composed of two applications at two different levels of the grid. At the high voltage level, we optimize operations using a stochastic unit commitment (SUC) model with hybrid time resolution. The SUC problem is solved with an asynchronous distributed subgradient method, for which we propose stepsize scaling and fast initialization techniques. The asynchronous algorithm is implemented in a high-performance computing cluster and benchmarked against a deterministic unit commitment model with exogenous reserve targets in an industrial scale test case of the Central Western European system (679 buses, 1037 lines, and 656 generators). At the distribution network level, we manage demand response from small clients through distributed stochastic control, which enables harnessing residential demand response while respecting the desire of consumers for control, privacy, and simplicity. The distributed stochastic control scheme is successfully tested on a test case with 10,000 controllable devices. Both applications demonstrate the potential for efficiently managing flexible resources in smart grids and for systematically coping with the uncertainty and variability introduced by renewable energy

    Virtual Environments for multiphysics code validation on Computing Grids

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    We advocate in this paper the use of grid-based infrastructures that are designed for seamless approaches to the numerical expert users, i.e., the multiphysics applications designers. It relies on sophisticated computing environments based on computing grids, connecting heterogeneous computing resources: mainframes, PC-clusters and workstations running multiphysics codes and utility software, e.g., visualization tools. The approach is based on concepts defined by the HEAVEN* consortium. HEAVEN is a European scientific consortium including industrial partners from the aerospace, telecommunication and software industries, as well as academic research institutes. Currently, the HEAVEN consortium works on a project that aims to create advanced services platforms. It is intended to enable "virtual private grids" supporting various environments for users manipulating a suitable high-level interface. This will become the basis for future generalized services allowing the integration of various services without the need to deploy specific grid infrastructures
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