TY - GEN
T1 - Autonomous driving vehicle controlling network using dynamic migrated edge computer function
AU - Yamanaka, Naoaki
AU - Yamamoto, Goki
AU - Okamoto, Satoru
AU - Muranaka, Takayuki
AU - Fumagalli, Andrea
N1 - Funding Information:
The author would like to thank Dr. Hidetoshi Takeshita of Keio University for his support in the experiments. This work is partly supported by the reconfigurable packet lambda project funded by the National Institute of Information and Communications Technology (NICT) Japan, JSPS KAKENHI Grant Number JP17H03269.
Funding Information:
The author would like to thank Dr. Hidetoshi Takeshita of Keio University for his support in the experiments.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - Autonomous driving vehicle control by edge computer network having very short response time has been proposed. Each vehicle has an agent program on the edge and automatically moved to adjacent edge computer following to the vehicle movement. On the edge computer, the agent program is processing with other vehicles' agents in a cyber network. We employ triple redundancy and majority rule to achieve high-reliability and less than 10 ms control latency try to be guaranteed. In addition, each vehicle has an IoT sensor including fine-GPS, so all precious position and speed of the vehicle can be monitored. We constructed the autonomous driving experimental course, the autonomous driving vehicle, and the edge computer system with the center cloud and tested in the campus test bed. According to the vehicle movement, network orchestrator setup a new optical path automatically and send the agent program to the adjacent target edge computer. This orchestration function is newly proposed application triggered dynamic optical network. In this presentation, I will show the detailed experimental results. This architecture and experimental results can be applied to the future smart and connected community.
AB - Autonomous driving vehicle control by edge computer network having very short response time has been proposed. Each vehicle has an agent program on the edge and automatically moved to adjacent edge computer following to the vehicle movement. On the edge computer, the agent program is processing with other vehicles' agents in a cyber network. We employ triple redundancy and majority rule to achieve high-reliability and less than 10 ms control latency try to be guaranteed. In addition, each vehicle has an IoT sensor including fine-GPS, so all precious position and speed of the vehicle can be monitored. We constructed the autonomous driving experimental course, the autonomous driving vehicle, and the edge computer system with the center cloud and tested in the campus test bed. According to the vehicle movement, network orchestrator setup a new optical path automatically and send the agent program to the adjacent target edge computer. This orchestration function is newly proposed application triggered dynamic optical network. In this presentation, I will show the detailed experimental results. This architecture and experimental results can be applied to the future smart and connected community.
KW - 5G network
KW - Autonomous driving
KW - Cyber physical
KW - Edge computing
KW - IoT
KW - Live migration
UR - http://www.scopus.com/inward/record.url?scp=85073070921&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073070921&partnerID=8YFLogxK
U2 - 10.1109/ICTON.2019.8840520
DO - 10.1109/ICTON.2019.8840520
M3 - Conference contribution
AN - SCOPUS:85073070921
T3 - International Conference on Transparent Optical Networks
BT - 21st International Conference on Transparent Optical Networks, ICTON 2019
PB - IEEE Computer Society
T2 - 21st International Conference on Transparent Optical Networks, ICTON 2019
Y2 - 9 July 2019 through 13 July 2019
ER -