TY - GEN
T1 - SDN based content-centric QoS-guaranteed for wireless multimedia sensor networks
AU - Li, Gaolei
AU - Wu, Jun
AU - Li, Jianhua
AU - Wang, Kuan
AU - He, Shan
N1 - Funding Information:
Acknowledgments. This work was supported by the National Science Foundation of China (Grant No. 61401273 and 61431008) and Shanghai Science and Technology Committee (Grant No. 15PJ1433800 and 14DZ1104903).
Publisher Copyright:
© 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2018
Y1 - 2018
N2 - As the deployment of wireless multimedia sensor networks (WMSNs) increases sharply, the control granularity of traditional quality of service (QoS) technologies present weak assistance to satisfy the various application requirements. In this paper, we propose a novel architecture of software-defined network (SDN) based content-centric QoS-guaranteed (SCQG) for WMSNs. The SDN is an innovative network paradigm, which has capability to uniformly monitor and control the WMSNs’ infrastructures automatically. In proposed architecture, we formulate proper priority for each content based on its popularity in WMSNs. And also, we extend the SDN controller to match the content and make flow tables each content requests. Besides, we design an k-nearest neighbor (KNN) based machine-learning algorithm to identify the popularity of different contents.
AB - As the deployment of wireless multimedia sensor networks (WMSNs) increases sharply, the control granularity of traditional quality of service (QoS) technologies present weak assistance to satisfy the various application requirements. In this paper, we propose a novel architecture of software-defined network (SDN) based content-centric QoS-guaranteed (SCQG) for WMSNs. The SDN is an innovative network paradigm, which has capability to uniformly monitor and control the WMSNs’ infrastructures automatically. In proposed architecture, we formulate proper priority for each content based on its popularity in WMSNs. And also, we extend the SDN controller to match the content and make flow tables each content requests. Besides, we design an k-nearest neighbor (KNN) based machine-learning algorithm to identify the popularity of different contents.
KW - Content-centric QoS-guaranteed
KW - k-nearest neighbor (KNN)
KW - Popularity
KW - Software-defined network (SDN)
KW - Wireless multimedia sensor networks (WMSNs)
UR - http://www.scopus.com/inward/record.url?scp=85041518862&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041518862&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-74176-5_4
DO - 10.1007/978-3-319-74176-5_4
M3 - Conference contribution
AN - SCOPUS:85041518862
SN - 9783319741758
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 40
EP - 48
BT - Industrial Networks and Intelligent Systems - 3rd International Conference, INISCOM 2017, Proceedings
A2 - Chen, Yuanfang
A2 - Duong, Trung Q.
PB - Springer Verlag
T2 - 3rd International Conference on Industrial Networks and Intelligent Systems, INISCOM 2017
Y2 - 4 September 2017 through 4 September 2017
ER -