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Distributed Computing and Artificial Intelligence pp 355–361Cite as

Grid Computing and CBR Deployment: Monitoring Principles for a Suitable Engagement

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 151))

Abstract

This paper presents a mathematical technique for modeling the generation of Grid-solutions employing a Case based reasoning system (CBR). Roughly speaking, an intelligent system that tries to be adapted to highly dynamic environment needs an efficient integration of high-level processes (deliberative and time-costly) within low-level (reactive, faster but poorer in quality) processes. The most relevant aspect of our current approach is that, unexpectedly, the performance of the CBR-system do not get worse any time that it retrieves worse cases in situations even when it has enough time to generate better solutions. We concentrate on formal aspects of the proposed Grid-CBR system without establishing which should be the most adequate procedure in a subsequent implementation stage. The advantage of the presented scheme is that it does not depend on neither the particular problem nor a concrete environment. It consists in a formal approach that only requires, on one hand, local information about the averaged-time spent by the system in obtaining a solution and, on the other hand, an estimation about their temporal restrictions. The potential use of industry standard technologies to implement such a Grid-enabled CBR system is discussed here too.

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Author information

Authors and Affiliations

  1. Industrial Engineering Dpt., Universidad Nacional de Colombia, Bogotá, Colombia

    Luis F. Castillo

  2. Computer Science and Systems Engineering Dpt., Universidad de Caldas, Manizales, Colombia

    Luis F. Castillo & Gustavo Isaza

  3. Computer Science Dpt, Universidad de Zaragoza, Spain, Saragossa

    Manuel Glez Bedia & Miguel Aguilera

  4. Systems Engineering, Universidad Autónoma de Manizales, Manizales, Colombia

    Juan David Correa

Authors
  1. Luis F. Castillo
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  2. Gustavo Isaza
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  3. Manuel Glez Bedia
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  4. Miguel Aguilera
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  5. Juan David Correa
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Corresponding author

Correspondence to Luis F. Castillo .

Editor information

Editors and Affiliations

  1. Dept. Computer Science &, Intelligent Systems, Osaka Prefecture University, Gakuen-chu 1-1, Sakai, Osaka, 599-8531, Japan

    Sigeru Omatu

  2. , Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan F. De Paz Santana

  3. , Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Sara Rodríguez González

  4. Escuela Politécnica Superior (EPS), Depto. Informática, Universidad Carlos III de Madrid, Avenida de la Universidad Carloss III 22, Madrid, 28270, Spain

    Jose M. Molina

  5. , Data Processing and Simulation Group, Universidad Politécnica de Madrid, Calle de Ramiro de Maeztu, 7, Madrid, 28040, Spain

    Ana M. Bernardos

  6. Faculty of Science, Department of Computing Science, University of Salamanca, Plaza de la Merced S/N, Salamanca, 37008, Spain

    Juan M. Corchado Rodríguez

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© 2012 Springer-Verlag Berlin Heidelberg

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Castillo, L.F., Isaza, G., Bedia, M.G., Aguilera, M., Correa, J.D. (2012). Grid Computing and CBR Deployment: Monitoring Principles for a Suitable Engagement. In: Omatu, S., De Paz Santana, J., González, S., Molina, J., Bernardos, A., Rodríguez, J. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28765-7_42

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  • DOI: https://doi.org/10.1007/978-3-642-28765-7_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28764-0

  • Online ISBN: 978-3-642-28765-7

  • eBook Packages: EngineeringEngineering (R0)

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