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Scalable Cloud-Based Data Storage Platform for Smart Grid

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Smart Grid Inspired Future Technologies (SmartGift 2017)

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Abstract

Real-time conditional monitoring and instinctive fault diagnosis plays an important role in the smart grid systems. Conventional data storage and management systems are facing the difficulties with the disseminated, heterogeneous and large volume of data. Conventional data management infrastructure utilizes centralized approach which comprises of large-scale server, disk array data storage hardware and relational database management system (RDBMS) for database services. This type of infrastructure may result in poor performance to support the requirement of smart grid applications for very large database with high data request rates at very low latency. Precise, fast, vulnerable and cooperative information system is the basis requirement for the smart grid applications. In this paper, we proposed a distributed data storage and management platform which guarantees high scalability and reliability data storage and management with the huge amount of information in the smart grid application. In order to evaluate and validate our scalable cloud-based data storage platform for smart grid, we deployed our proposed infrastructure in our cyber-physical test-bed which is a facility to test innovative technologies for building efficiency and urban sustainability.

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Acknowledgement

This research is funded by the Republic of Singapore’s National Research Foundation through a grant to the Berkeley Education Alliance for Research in Singapore (BEARS) for the Singapore-Berkeley Building Efficiency and Sustainability in the Tropics (SinBerBEST) Program. BEARS has been established by the University of California, Berkeley as a center for intellectual excellence in research and education in Singapore.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Hnin Yu Shwe & Soong Boon Hee

  2. Department of Electrical and Electronic Engineering, Auckland University of Technology, Auckland, New Zealand

    Peter Han Joo Chong

Authors
  1. Hnin Yu Shwe
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  2. Soong Boon Hee
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  3. Peter Han Joo Chong
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Corresponding author

Correspondence to Hnin Yu Shwe .

Editor information

Editors and Affiliations

  1. Queen Mary University of London, London, United Kingdom

    Eng Tseng Lau

  2. Queen Mary University of London, London, United Kingdom

    Michael K.K. Chai

  3. Queen Mary University of London, London, United Kingdom

    Yue Chen

  4. Austrian Institute of Technology, Vienna, Austria

    Oliver Jung

  5. University of British Columbia, Vancouver, British Columbia, Canada

    Victor C.M. Leung

  6. University of Essex, Colchester, United Kingdom

    Kun Yang

  7. Austrian Institute of Technology, Vienna, Austria

    Sandford Bessler

  8. Middlesex University London, London, United Kingdom

    Jonathan Loo

  9. University of Tsukuba, Ibaraki, Japan

    Tomonori Nakayama

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Shwe, H.Y., Hee, S.B., Chong, P.H.J. (2017). Scalable Cloud-Based Data Storage Platform for Smart Grid. In: Lau, E., et al. Smart Grid Inspired Future Technologies. SmartGift 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-319-61813-5_26

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  • DOI: https://doi.org/10.1007/978-3-319-61813-5_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61812-8

  • Online ISBN: 978-3-319-61813-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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