Dataflow Management Platform for Smart Communities using an Edge Computing Environment

Shogo Shimahara, Hiroaki Nishi

研究成果: Conference contribution

抄録

As various data services are provided to realize Society 5.0, the usage of personal data is estimated to increase along with the explosive increase in data traffic. It is important that the protection of privacy keeps pace with increases in the exchange of data containing personal information. Starting from the enforcement of the General Data Protection Regulation (GDPR), stricter privacy protection regulations are expanding to more countries. These restrictions require that personal data should be hidden or anonymized before they are propagated over the network. The secondary usage of data is assumed in smart communities, and systems that can protect privacy are required for secure network infrastructures. In this study, we propose an edge-based computing platform that manages the privacy of users on the network of a smart community. For the platform, we prepared three models: The Basic, Preceding Packet, and Piggyback models. These are considered OpenFlow models, and the network efficiency for each was evaluated.

本文言語English
ホスト出版物のタイトルIECON 2021 - 47th Annual Conference of the IEEE Industrial Electronics Society
出版社IEEE Computer Society
ISBN(電子版)9781665435543
DOI
出版ステータスPublished - 2021 10月 13
イベント47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021 - Toronto, Canada
継続期間: 2021 10月 132021 10月 16

出版物シリーズ

名前IECON Proceedings (Industrial Electronics Conference)
2021-October

Conference

Conference47th Annual Conference of the IEEE Industrial Electronics Society, IECON 2021
国/地域Canada
CityToronto
Period21/10/1321/10/16

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 電子工学および電気工学

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