Geolocation-Centric Information Platform for Resilient Spatio-temporal Content Management

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  • TSUKAMOTO Kazuya
    Department of Computer Science and Electronics, Kyushu Institute of Technology (KIT)
  • TAMURA Hitomi
    Department of Information Electronics, Fukuoka Institute of Technology (FIT)
  • TAENAKA Yuzo
    Graduate School of Science and Technology, Nara Institute of Science and Technology (NAIST)
  • NOBAYASHI Daiki
    Department of Electrical Engineering and Electronics, Faculty of Engineering, KIT
  • YAMAMOTO Hiroshi
    Department of Information Science and Engineering, Ritsumeikan University
  • IKENAGA Takeshi
    Department of Electrical Engineering and Electronics, Faculty of Engineering, KIT
  • LEE Myung
    Department of Electrical and Computer Engineering, City University of New York (CCNY)

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<p>In IoT era, the growth of data variety is driven by cross-domain data fusion. In this paper, we advocate that “local production for local consumption (LPLC) paradigm” can be an innovative approach in cross-domain data fusion, and propose a new framework, geolocation-centric information platform (GCIP) that can produce and deliver diverse spatio-temporal content (STC). In the GCIP, (1) infrastructure-based geographic hierarchy edge network and (2) adhoc-based STC retention system are interplayed to provide both of geolocation-awareness and resiliency. Then, we discussed the concepts and the technical challenges of the GCIP. Finally, we implemented a proof-of-concepts of GCIP and demonstrated its efficacy through practical experiments on campus IPv6 network and simulation experiments.</p>

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