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Geolocation-Centric Information Platform for Resilient Spatio-temporal Content Management
Kazuya TSUKAMOTO Hitomi TAMURA Yuzo TAENAKA Daiki NOBAYASHI Hiroshi YAMAMOTO Takeshi IKENAGA Myung LEE
IEICE TRANSACTIONS on Communications
Publication Date: 2021/03/01
Online ISSN: 1745-1345
Type of Manuscript: INVITED PAPER (Special Section on Fusion of Network Virtualization/Softwarization and Artificial Intelligence towards Beyond-5G Innovative IoT Services)
geolocation-centric, cross-domain data fusion, local production for local consumption,
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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.