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ICENI: Optimisation of Component Applications within a Grid Environment

Available data suggest that, in addition to the obvious catches of fish for human needs, the by- catches in the world’s fisheries have a significant ecological impact and cause mortality amongst fin-fish (particularly the juveniles of commercial fish species), as well as amongst benthic invertebrates, marine mammals, turtles and birds. FAO estimated recently that world-wide, the by-catch discarded in the commercial fisheries amounts to around 20 million metric tons and accounts for economic losses that run into billions of dollars annually (in terms of the potential value which could be realized if, a few years later the discarded juveniles were to. | ICENI Optimisation of Component Applications within a Grid Environment Nathalie Furmento Anthony Mayer Stephen McGough Steven Newhouse Tony Field and John Darlington London e-Seienee Centre. Imperial College of Science Technology and Medicine uo Queen s Gate London SW7 SBZ. UK lescSic.ac.uk http ww.lesc.ic.ac.uk Abstract Effective exploitation of Computational Grids can only be achieved when applications are fully integrated with the Grid middleware and the underlying compute-tional resources. Fundamental to this exploitation is information. Information about the structure and behaviour of the application the capability of the computational and networking resources and the availability and access to these resources by an individual a group or an organisation. In this paper we describe ICENI Imperial College e-Science Networked Infrastructure a Grid middleware framework developed within the London e-Science Centre. ICENI is a platform independent framework that uses open and extensible XML derived protocols within a framework built using Java and Jini to explore effective application execution upon distributed federated resources. We match a high-level application specification defined as a network of components to an optimal combination of the currently available component implementations within our Grid environment by utilising a system of composite performance modelling. We demonstrate the effectiveness of this architecture through high-level specification and solution of a set of linear equations by automatic and optimal resource and implementation selection. 1 Introduction Computational Grids federations of geographically distributed heterogeneous hardware and software resources are emerging in academia between national research laboratories and within commercial organisations. Eventually these computing resources will become ubiquitous and appear transparent to the user delivering computational power to applications in the same manner as Preprint submitted to