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

Autor: Takeshi Ikenaga, Yuzo Taenaka, Hitomi Tamura, Kazuya Tsukamoto, Myung J. Lee, Daiki Nobayashi, Hiroshi Yamamoto
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: IEICE Transactions on Communications. (3):199-209
ISSN: 0916-8516
Popis: 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.
Databáze: OpenAIRE