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Prediction of Failure Risk Through Logical Decision Trees in Web Service Compositions

  • Byron Portilla-RoseroEmail author
  • Jaime A. Guzmán
  • Giner Alor-Hernández
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 152)

Abstract

In a service composition, the Quality of Services can be useful to identify those hidden data for a traditional composition; they can be a decisive factor for determining the behavior of future compositions since they allow evaluating risks resulting from reasons totally dependent on both the service environment and/or the composition system. Importance of this data is reflected on the way they are obtained, estimated, and applied to a composition. This paper has specifically studied the following three characteristics: availability, reactivity of services in periods of time, and management of beliefs to determine influence of services composition and to determine failure risk in such a composition through machine learning.

Keywords

Service Composition Service Failure Failure Risk Service Execution Composition Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This paper is supported by the project “programa de fortalecimiento del grupo de investigación Sistemas Inteligentes Web—SINTELWEB” quipu code 20201009532.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Byron Portilla-Rosero
    • 1
    Email author
  • Jaime A. Guzmán
    • 1
  • Giner Alor-Hernández
    • 2
  1. 1.School of SystemsUniversidad Nacional de ColombiaMedellínColombia
  2. 2.Division of Research and Postgraduate StudiesInstituto Tecnológico de OrizabaOrizabaMexico

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