TY - GEN
T1 - Edge learning based green content distribution for information-centric internet of things
AU - Shen, Qili
AU - Wu, Jun
AU - Li, Jianhua
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Being the revolutionary future networking architecture, information-centric networking (ICN) conducts network distribution based on content, which is ideally suitable for Internet of things (IoT). With the rapid growth of network traffic, compared to the conventional IoT, information-centric Internet of things (IC-IoT) is expected to provide users with the better satisfaction of the network quality of service (QoS). However, due to IC-IoT requirements of low latency, large data volume, marginalization, and intelligent processing, it urgently needs an efficient content distribution system. In this paper, we propose an edge learning based green content distribution scheme for IC-IoT. We implement intelligent path selection based on decision tree and edge calculation. Moreover, we apply distributed coding based content transmission to enhance the speed and recovery capability of content. Meanwhile, we have verified the effectiveness and performance of this scheme based on a large number of simulation experiments. The work of this paper is of great significance to improve the efficiency and flexibility of content distribution in IC-IoT.
AB - Being the revolutionary future networking architecture, information-centric networking (ICN) conducts network distribution based on content, which is ideally suitable for Internet of things (IoT). With the rapid growth of network traffic, compared to the conventional IoT, information-centric Internet of things (IC-IoT) is expected to provide users with the better satisfaction of the network quality of service (QoS). However, due to IC-IoT requirements of low latency, large data volume, marginalization, and intelligent processing, it urgently needs an efficient content distribution system. In this paper, we propose an edge learning based green content distribution scheme for IC-IoT. We implement intelligent path selection based on decision tree and edge calculation. Moreover, we apply distributed coding based content transmission to enhance the speed and recovery capability of content. Meanwhile, we have verified the effectiveness and performance of this scheme based on a large number of simulation experiments. The work of this paper is of great significance to improve the efficiency and flexibility of content distribution in IC-IoT.
KW - Content distribution
KW - Distributed coding
KW - Edge learning
KW - IC-IoT
KW - Intelligent
UR - http://www.scopus.com/inward/record.url?scp=85071067800&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071067800&partnerID=8YFLogxK
U2 - 10.1109/TSP.2019.8769084
DO - 10.1109/TSP.2019.8769084
M3 - Conference contribution
AN - SCOPUS:85071067800
T3 - 2019 42nd International Conference on Telecommunications and Signal Processing, TSP 2019
SP - 67
EP - 70
BT - 2019 42nd International Conference on Telecommunications and Signal Processing, TSP 2019
A2 - Herencsar, Norbert
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd International Conference on Telecommunications and Signal Processing, TSP 2019
Y2 - 1 July 2019 through 3 July 2019
ER -