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International Conference on Knowledge Engineering and the Semantic Web

KESW 2014: Knowledge Engineering and the Semantic Web pp 29–43Cite as

Cloud Sensor Ontology and Linked Data to Support Autonomicity in Cloud Application Platforms

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 468))

Abstract

Cloud application platforms with their numerous deployed applications, platform and third-party services are becoming increasingly complex, dynamic and data-intensive, and require novel intelligent approaches to be applied in order to maintain them at an operational level. By treating cloud application platforms as distributed networks of software sensors and utilising techniques from the Semantic Sensor Web area, we have developed a monitoring framework which allows us to detect, diagnose and react to emerging critical situations in complex environments of cloud application platforms in a dynamic manner. In this paper, we focus on our use of a Sensor Cloud Ontology to: (i) represent cloud-based logical software sensors; (ii) homogenise monitored sensor data in the form of RDF streams; and (iii) apply stream and static reasoning to these monitored values in order to detect critical situations. We also explain how utilisation of Linked Data principles can help achieve a more flexible and extensible architecture to define diagnosis and adaptation policies. We discuss benefits associated with our approach, as well as potential shortcomings and challenges.

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Author information

Authors and Affiliations

  1. South-East European Research Centre (SEERC), CITY College — International Faculty of the University of Sheffield, Thessaloniki, Greece

    Rustem Dautov & Iraklis Paraskakis

  2. Department of Computer Science, University of Sheffield, UK

    Mike Stannett

Authors
  1. Rustem Dautov
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  2. Iraklis Paraskakis
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  3. Mike Stannett
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Editor information

Editors and Affiliations

  1. University of Ulm, Institute of Artificial Intelligence, 89069, Ulm, Germany

    Pavel Klinov

  2. Mechanics and Optics, Saint Petersburg National Research University of Information Technologies, Saint-Petersburg, Russia

    Dmitry Mouromtsev

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© 2014 Springer International Publishing Switzerland

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Dautov, R., Paraskakis, I., Stannett, M. (2014). Cloud Sensor Ontology and Linked Data to Support Autonomicity in Cloud Application Platforms. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and the Semantic Web. KESW 2014. Communications in Computer and Information Science, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-319-11716-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-11716-4_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11715-7

  • Online ISBN: 978-3-319-11716-4

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