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International Congress on High-Performance Computing and Big Data Analysis

TopHPC 2019: High-Performance Computing and Big Data Analysis pp 132–142Cite as

Distributed-to-Centralized Data Management Through Data LifeCycle Models for Zero Emission Neighborhoods

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 891))

Abstract

Data management and organization in context have been highlighted as a complex scenario during their entire life cycle (DLC) models by several research groups. Similarly, smart city has been faced several challenges and complexities to organize the obtained data from data sources across the city. Currently, there are two main references for the data management architecture in the smart city scenarios, Centralized Data Management (CDM) and Distributed-to-Centralized Data Management (D2C-DM). In this paper, we developed our proposed hierarchical D2C-DM architecture for Zero Emission Neighborhoods (ZEN) center in Norway. In the beginning, we extend the proposed Data LifeCycle model (DLC) for smart city scenario concerning the ZEN Key Performance Indicators (KPI) and their required business models. Afterward, we map the ZEN DLC model to our proposed D2C-DM for smart city, including the ZEN center. In addition, the fully hierarchical D2C architecture has the potential to organize all data life cycle stages from data production to data consumption across the city on the smart city scenarios. Finally, we discuss and conclude several capabilities of the proposed D2C-DM through the related DLC models in the ZEN center scenario, such as: (i) using all benefits of data management architectures from distributed to centralizes schema simultaneously and in one unified architecture; (ii) handling all different obtained data types (including real-time, last-recent, and historical data) in smart cities and the ZEN data types (consisting of the context, research, and KPI data) each cross-layer (from IoT devices to Cloud technologies) of the architecture.

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Acknowledgment

This paper has been written within the Research Centre on Zero Emission Neighborhoods in smart cities (FME ZEN). The authors gratefully acknowledge the support from the ZEN partners and the Research Council of Norway.

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Authors and Affiliations

  1. Department of Computer Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway

    Amir Sinaeepourfard & Sobah Abbas Petersen

Authors
  1. Amir Sinaeepourfard
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  2. Sobah Abbas Petersen
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Corresponding author

Correspondence to Amir Sinaeepourfard .

Editor information

Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Lucio Grandinetti

  2. Kharazmi University, Tehran, Iran

    Seyedeh Leili Mirtaheri

  3. University of Calabria, Rende, Italy

    Reza Shahbazian

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Sinaeepourfard, A., Petersen, S.A. (2019). Distributed-to-Centralized Data Management Through Data LifeCycle Models for Zero Emission Neighborhoods. In: Grandinetti, L., Mirtaheri, S., Shahbazian, R. (eds) High-Performance Computing and Big Data Analysis. TopHPC 2019. Communications in Computer and Information Science, vol 891. Springer, Cham. https://doi.org/10.1007/978-3-030-33495-6_11

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  • DOI: https://doi.org/10.1007/978-3-030-33495-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33494-9

  • Online ISBN: 978-3-030-33495-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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