TY - GEN
T1 - OpenStack-based highly scalable IoT/M2M platforms
AU - De La Bastida, David
AU - Lin, Fuchun
PY - 2018/1/30
Y1 - 2018/1/30
N2 - The IoT/M2M platforms are emerging to provide a common service layer for various types of new IoT applications. It is foreseen billions of IoT/M2M devices will soon be connected to those IoT/M2M platforms hosted in the cloud. In this research we propose a highly scalable OpenStack-based architecture for IoT/M2M platforms. Our unique contribution consists of leveraging the advanced functionalities of OpenStack to introduce a master node specifically designed for IoT/M2M scalability in the cloud and a load balancing queue node cooperating with the master node for fair distribution of incoming traffic among platform nodes. Using four different types of IoT/M2M applications: smart meter, Bluetooth tags, eHealth, and video, we show that compared to LBAAS and Heat that are OpenStack native load balancing and scalability functions, in most cases our proposed system is capable of achieving the fastest response time and the lowest computational cost with acceptable tradeoff of more energy consumption.
AB - The IoT/M2M platforms are emerging to provide a common service layer for various types of new IoT applications. It is foreseen billions of IoT/M2M devices will soon be connected to those IoT/M2M platforms hosted in the cloud. In this research we propose a highly scalable OpenStack-based architecture for IoT/M2M platforms. Our unique contribution consists of leveraging the advanced functionalities of OpenStack to introduce a master node specifically designed for IoT/M2M scalability in the cloud and a load balancing queue node cooperating with the master node for fair distribution of incoming traffic among platform nodes. Using four different types of IoT/M2M applications: smart meter, Bluetooth tags, eHealth, and video, we show that compared to LBAAS and Heat that are OpenStack native load balancing and scalability functions, in most cases our proposed system is capable of achieving the fastest response time and the lowest computational cost with acceptable tradeoff of more energy consumption.
KW - Cloud computing
KW - Internet of things
KW - Machine to machine communications
KW - OpenStack
KW - Scalability
UR - http://www.scopus.com/inward/record.url?scp=85047432157&partnerID=8YFLogxK
U2 - 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.110
DO - 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.110
M3 - Conference contribution
AN - SCOPUS:85047432157
T3 - Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017
SP - 711
EP - 718
BT - Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017
A2 - Min, Geyong
A2 - Jin, Xiaolong
A2 - Yang, Laurence T.
A2 - Wu, Yulei
A2 - Georgalas, Nektarios
A2 - Al-Dubi, Ahmed
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Joint 10th IEEE International Conference on Internet of Things, iThings 2017, 13th IEEE International Conference on Green Computing and Communications, GreenCom 2017, 10th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2017 and the 3rd IEEE International Conference on Smart Data, Smart Data 2017
Y2 - 21 June 2017 through 23 June 2017
ER -
