TY - GEN
T1 - Dynamic Congestion Control in Information-Centric Networking Utilizing Sensors for the IoT
AU - Sukjaimuk, Rungrot
AU - Nguyen, Quang N.
AU - Sato, Takuro
N1 - Funding Information:
ACKNOWLEDGMENT This study has been supported by the Royal Thai Government initiated by the National Science and Technology Development Agency and coordinated by the Office of The Civil Service Commission.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Network congestion control is an important criterion to evaluate the network performance. This is a major research challenge in ICN (Information-Centric Networking), especially in the case of high congestion in a Sensor Network for the IoT (Internet of Things). The reason is that the content producers in ICN need to reply a huge number of content requests from the consumers. In this paper, we propose a hierarchical ICN model for IoT sensor network with dynamic congestion control mechanism. The proposed network system transmits the content with content popularity and priority-based delay time, together with adaptive content lifetime and cache management strategy. The evaluation results using ndnSIM show that the proposed model can provide higher network performance efficiency for the future Internet by achieving higher throughput with lower Interest packet drop rate and higher cache hit rate as we increase the number of IoT sensors in ICN.
AB - Network congestion control is an important criterion to evaluate the network performance. This is a major research challenge in ICN (Information-Centric Networking), especially in the case of high congestion in a Sensor Network for the IoT (Internet of Things). The reason is that the content producers in ICN need to reply a huge number of content requests from the consumers. In this paper, we propose a hierarchical ICN model for IoT sensor network with dynamic congestion control mechanism. The proposed network system transmits the content with content popularity and priority-based delay time, together with adaptive content lifetime and cache management strategy. The evaluation results using ndnSIM show that the proposed model can provide higher network performance efficiency for the future Internet by achieving higher throughput with lower Interest packet drop rate and higher cache hit rate as we increase the number of IoT sensors in ICN.
KW - Dynamic Congestion Control
KW - FI (Future Internet)
KW - ICN (Information-Centric Networking)
KW - IoT (Internet of Things)
KW - Sensor Networking
UR - http://www.scopus.com/inward/record.url?scp=85065080057&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85065080057&partnerID=8YFLogxK
U2 - 10.1109/TENCONSpring.2018.8691983
DO - 10.1109/TENCONSpring.2018.8691983
M3 - Conference contribution
AN - SCOPUS:85065080057
T3 - 2018 IEEE Region 10 Symposium, Tensymp 2018
SP - 63
EP - 68
BT - 2018 IEEE Region 10 Symposium, Tensymp 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Region 10 Symposium, Tensymp 2018
Y2 - 1 July 2018 through 6 July 2018
ER -