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Generic Model for Adaptable Caching in the Knowledge-Oriented Web Engineering

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Knowledge Science, Engineering and Management (KSEM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9983))

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Abstract

Web applications represent a commonly used type of technology in many domains. They are applied for various knowledge-intensive purposes ranging from the external marketing activities to the internal content presentation. Therefore, the speed in which they can be utilised represents quite significant variable of their evaluation. Based on the domain knowledge expressed in a form of generic model this paper presents a possibility of the adaptable cache utilisation. The model is based on existing technologies and its aim is to significantly reduce data load and time demands associated with the use of web pages. The model is implemented in practice with various fragments of codes provided in text. This implementation is consequently tested by means of the three most common types of web pages. Acquired results prove significant reduction of data load in comparison with the traditional request-response model. The paper also outlines directions for further research in this area.

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Acknowledgements

The support of the FIM UHK Specific Research Project “Solution of production, transportation and allocation problems in agent-based models” is gratefully acknowledged.

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Authors and Affiliations

  1. Faculty of Informatics and Management, University of Hradec Králové, Rokitanského 62, Hradec Králové, Czech Republic

    Jiří Štěpánek & Vladimír Bureš

Authors
  1. Jiří Štěpánek
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  2. Vladimír Bureš
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Corresponding author

Correspondence to Vladimír Bureš .

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Editors and Affiliations

  1. University of Passau, Passau, Germany

    Franz Lehner

  2. University of Passau , Passau, Germany

    Nora Fteimi

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Štěpánek, J., Bureš, V. (2016). Generic Model for Adaptable Caching in the Knowledge-Oriented Web Engineering. In: Lehner, F., Fteimi, N. (eds) Knowledge Science, Engineering and Management. KSEM 2016. Lecture Notes in Computer Science(), vol 9983. Springer, Cham. https://doi.org/10.1007/978-3-319-47650-6_20

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  • DOI: https://doi.org/10.1007/978-3-319-47650-6_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47649-0

  • Online ISBN: 978-3-319-47650-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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