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Weaving Open Services with Runtime Models for Continuous Smart Cities KPIs Assessment

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Service-Oriented Computing (ICSOC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 13121))

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Abstract

The automatic Key Performance Indicators (KPIs) assessment for smart cities is challenging, since the input parameters needed for the KPIs calculations are highly dynamic and change with different frequencies. Moreover, they are provided by heterogeneous data sources (e.g., IoT infrastructures, Web Services, open repositories), with different access protocol. Open services are widely adopted in this area on top of open data, IoT, and cloud services. However, KPIs assessment frameworks based on smart city models are currently decoupled from open services. This limits the possibility of having runtime up-to-date data for KPIs assessment and synchronized reports. Thus, this paper presents a generic service-oriented middleware that connects open services and runtime models, applied to a model-based KPIs assessment framework for smart cities. It enables a continuous monitoring of the KPIs’ input parameters provided by open services, automating the data acquisition process and the continuous KPIs evaluation. Experiment shows how the evolved framework enables a continuous KPIs evaluation, by drastically decreasing (\(\sim \)88%) the latency compared to its baseline.

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Notes

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  3. 3.

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  4. 4.

    https://www.breezometer.com/.

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    https://bit.ly/3lc1GHG.

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    https://github.com/iovinoludovico/runtime-kpi-assessment.

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    https://www.eclipse.org/Xtext/.

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    https://bit.ly/3l8jL9s.

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    https://www.eclipse.org/epsilon/doc/eol/.

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    https://github.com/iovinoludovico/runtime-kpi-assessment.

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Acknowledgements

This work was partially supported by the Centre for Urban Informatics and Modelling (CUIM) and the PON Cultural Heritage-AIM1880573, National Projects at GSSI, and by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development (CDG).

Author information

Authors and Affiliations

  1. Gran Sasso Science Institute, L’Aquila, Italy

    Martina De Sanctis, Ludovico Iovino & Maria Teresa Rossi

  2. CDL-MINT, Johannes Kepler University, Linz, Austria

    Manuel Wimmer

Authors
  1. Martina De Sanctis
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  2. Ludovico Iovino
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  3. Maria Teresa Rossi
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  4. Manuel Wimmer
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Corresponding author

Correspondence to Martina De Sanctis .

Editor information

Editors and Affiliations

  1. Zayed University, Dubai, United Arab Emirates

    Hakim Hacid

  2. Technical University of Berlin, Berlin, Germany

    Odej Kao

  3. Informatica Automatica Gestio, Sapienza University of Rome, Rome, Italy

    Massimo Mecella

  4. Departement d'Informatique, University of Quebec, Montreal, QC, Canada

    Naouel Moha

  5. UNSW Sydney, Sydney, NSW, Australia

    Hye-young Paik

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De Sanctis, M., Iovino, L., Rossi, M.T., Wimmer, M. (2021). Weaving Open Services with Runtime Models for Continuous Smart Cities KPIs Assessment. In: Hacid, H., Kao, O., Mecella, M., Moha, N., Paik, Hy. (eds) Service-Oriented Computing. ICSOC 2021. Lecture Notes in Computer Science(), vol 13121. Springer, Cham. https://doi.org/10.1007/978-3-030-91431-8_43

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  • DOI: https://doi.org/10.1007/978-3-030-91431-8_43

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  • Online ISBN: 978-3-030-91431-8

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