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One of open issues in grid computing is efficient resource discovery. Centralized solutions have been proved inefficient for global scale resource discovery. In addition, due to lacking of semantic support, the discovery mechanisms of current solutions do not have the flexibility to perform flexible resource matches for requirements of tasks or jobs.
We will develop a portlet that allows us to create rapidly and deploy job submissions portlets based on user requirements. The requirements are captured by using the portlet to build a job submission interface. The job submission interface is itself a portlet and can be shown to end-users immediately. More specifically, a designer or software engineer creates a set of parameters with defaults and parameter sweeps. The tool translates this in to a portlet, which the developer is able to deploy dynamically in to the same GridSphere portal.
Multidisciplinary optimisation (MDO) problems bring together different professionals with diverse backgrounds to collaborate. These professionals are usually distributed in different geographical locations and often need to share resources such as data, information, algorithms, software, hardware, designs and expensive instruments among other things. Grid computing looks suitable for MDO applications with its distributed large-scale computational capabilities that enable virtual organisations to securely work together.
Volunteer Grids represent the most dynamic and unpredictable computing platform in the Grid space. Nodes may come and go, offer varying capabilities, and varying levels of reliability. Despite these "features" this is an attractive platform for scientific computing due to its scale and ease of management. Our research aim is to harness these open systems for a broader class of high performance e-science applications. We discuss one of the main obstacles to achieving this goal - how to effectively manage the inherent unreliability in the system.