Congestion-aware suspicious object detection system using information-centric networking

Xin Qi*, Toshio Sato, Keping Yu, Zheng Wen, San Hlaing Myint, Yutaka Katsuyama, Kiyohito Tokuda, Takuro Sato

*この研究の対応する著者

研究成果: Conference contribution

抄録

Deadly diseases and terrorist attacks are greatly threatening human safety, which challenges global security. To address this issue, urban surveillance systems are being applied at a rapid pace with mature but inefficient solutions in large scale networks. When a surveillance network is managing the data generated from multiple edge nodes, it is easy to create congestions due to concentrated data traffic and inefficient data delivery mechanism. In parallel, 5G technology, cope with explosive mobile data traffic growth and massive device connections, can realize a true 'Internet of Everything' and build the social and economical digital transformation. In this paper, in the context of 5G technology, we propose an Information-Centric Networking (ICN) surveillance system based on our designed Suspicious Object Network System (SONS) over the concept of next-generation networking. In this solution, the edge nodes in the network distribute the computing and data storage requirements. We first describe the current surveillance issues and our proposed system architecture. Then we use simulation to verify and evaluate the system performance between legacy all-to-one centralized surveillance system and ICN based decentralized surveillance system.

本文言語English
ホスト出版物のタイトル2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728197944
DOI
出版ステータスPublished - 2021 1 9
イベント18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021 - Virtual, Las Vegas, United States
継続期間: 2021 1 92021 1 13

出版物シリーズ

名前2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021

Conference

Conference18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021
国/地域United States
CityVirtual, Las Vegas
Period21/1/921/1/13

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • コンピュータ ビジョンおよびパターン認識

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