Abstract
A MDO framework is a collaborative distributed computing environment that facilitates the integration of multi-disciplinary design efforts to achieve the global optimum result among local mutually-conflicting optimum results on heterogeneous platforms throughout the entire design process. The challenge for the MDO framework is to support the integration of legacy software and data, workflow management, heterogeneous computing, parallel computing and fault tolerance at the same time. In this paper, we present a Linda tuple space-based distributed computing framework optimized for MDO which is called MEDIC. In the design of MEDIC, we classify required technologies and propose an architecture in which those technologies can be independently implememnted at different layers. The Linda tuple space allows us to make the MEDIC architecture simple because it provides a flexible computing platform where various distributed and parallel computing models are easily implemented in the same way, multi-agents are easily supported, and effective fault tolerance techniques are available. A prototype system of MEDIC has been developed and applied for building an integrated design environment for super-high temperature vacuum furnaces called iFUD.
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© 2005 Springer-Verlag Berlin Heidelberg
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Jin, S. et al. (2005). MEDIC: A MDO-Enabling Distributed Computing Framework. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_135
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DOI: https://doi.org/10.1007/11539506_135
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28312-6
Online ISBN: 978-3-540-31830-9
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