TY - GEN
T1 - Congestion-aware suspicious object detection system using information-centric networking
AU - Qi, Xin
AU - Sato, Toshio
AU - Yu, Keping
AU - Wen, Zheng
AU - Myint, San Hlaing
AU - Katsuyama, Yutaka
AU - Tokuda, Kiyohito
AU - Sato, Takuro
N1 - Funding Information:
This research has been supported by research grant for expanding radio wave resources (JPJ000254) of Ministry of Internal Affairs and Communications under contract for “Research and development of radar fundamental technology for advanced recognition of moving objects for security enhancement”.
Publisher Copyright:
© 2021 IEEE.
PY - 2021/1/9
Y1 - 2021/1/9
N2 - 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.
AB - 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.
KW - - ICN
KW - 5G
KW - Decentralization
KW - Next-gen network
KW - Surveillance system
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U2 - 10.1109/CCNC49032.2021.9369510
DO - 10.1109/CCNC49032.2021.9369510
M3 - Conference contribution
AN - SCOPUS:85102983010
T3 - 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
BT - 2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021
Y2 - 9 January 2021 through 13 January 2021
ER -
