TY - GEN
T1 - Prediction of QoS Outage Probability for Wireless Communication in Factory Environments
AU - Suga, Norisato
AU - Yano, Kazuto
AU - Webber, Julian
AU - Hou, Yafei
AU - Higashimori, Toshihide
AU - Suzuki, Yoshinori
N1 - Funding Information:
ACKNOWLEDGMENT This work is supported by Japan Ministry of Internal Affairs and Communications with the fund of “R&D on Technologies to Densely and Efficiently Utilize Radio Resources of Unlicensed Bands in Dedicated Areas.”
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - In manufacturing and logistics, various applications exploiting IoT devices are started to be used. Although there is a demand for wireless connection between the IoT devices to networks, obstacles such as radio frequency interference, multipath-rich propagation, and movement of objects make communication unstable. The instability can cause a system failure of IoT applications. Since the QoS outage does not occur frequently in actual systems, the training of QoS outage events may be insufficient to accurately predict future QoS values. Therefore, we propose a method to estimate QoS outage probability from the predicted future QoS, distribution of prediction error, and required QoS. The proposed method can achieve high estimation accuracy by obtaining and using different error distributions according to the rarity of the observed sequence. Simulation results based on a theoretical throughput analysis of wireless LAN show that the proposed method can appropriately predict the QoS outage probability.
AB - In manufacturing and logistics, various applications exploiting IoT devices are started to be used. Although there is a demand for wireless connection between the IoT devices to networks, obstacles such as radio frequency interference, multipath-rich propagation, and movement of objects make communication unstable. The instability can cause a system failure of IoT applications. Since the QoS outage does not occur frequently in actual systems, the training of QoS outage events may be insufficient to accurately predict future QoS values. Therefore, we propose a method to estimate QoS outage probability from the predicted future QoS, distribution of prediction error, and required QoS. The proposed method can achieve high estimation accuracy by obtaining and using different error distributions according to the rarity of the observed sequence. Simulation results based on a theoretical throughput analysis of wireless LAN show that the proposed method can appropriately predict the QoS outage probability.
KW - QoS outage
KW - probabilistic neural network
KW - probability prediction
KW - smart factory
UR - http://www.scopus.com/inward/record.url?scp=85084045649&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084045649&partnerID=8YFLogxK
U2 - 10.1109/IINTEC48298.2019.9112098
DO - 10.1109/IINTEC48298.2019.9112098
M3 - Conference contribution
AN - SCOPUS:85084045649
T3 - 2019 International Conference on Internet of Things, Embedded Systems and Communications, IINTEC 2019 - Proceedings
SP - 124
EP - 129
BT - 2019 International Conference on Internet of Things, Embedded Systems and Communications, IINTEC 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Conference on Internet of Things, Embedded Systems and Communications, IINTEC 2019
Y2 - 20 December 2019 through 22 December 2019
ER -