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Celimuge Wu
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Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning
X Chen, H Zhang, C Wu, S Mao, Y Ji, M Bennis
IEEE Internet of Things Journal 6 (3), 4005-4018, 2018
4052018
AVE: Autonomous vehicular edge computing framework with ACO-based scheduling
J Feng, Z Liu, C Wu, Y Ji
IEEE Transactions on Vehicular Technology 66 (12), 10660-10675, 2017
2322017
QoS-guarantee resource allocation for multibeam satellite industrial internet of things with NOMA
X Liu, XB Zhai, W Lu, C Wu
IEEE Transactions on Industrial Informatics 17 (3), 2052-2061, 2019
1732019
Edge computing in 5G: A review
N Hassan, KLA Yau, C Wu
IEEE Access 7, 127276-127289, 2019
1482019
Flexible, portable, and practicable solution for routing in VANETs: A fuzzy constraint Q-learning approach
C Wu, S Ohzahata, T Kato
IEEE Transactions on Vehicular Technology 62 (9), 4251-4263, 2013
1352013
Mobile edge computing for the internet of vehicles: Offloading framework and job scheduling
J Feng, Z Liu, C Wu, Y Ji
IEEE vehicular technology magazine 14 (1), 28-36, 2018
1092018
Performance optimization in mobile-edge computing via deep reinforcement learning
X Chen, H Zhang, C Wu, S Mao, Y Ji, M Bennis
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall), 1-6, 2018
1092018
Federated learning for vehicular internet of things: Recent advances and open issues
Z Du, C Wu, T Yoshinaga, KLA Yau, Y Ji, J Li
IEEE Open Journal of the Computer Society 1, 45-61, 2020
1042020
VANET broadcast protocol based on fuzzy logic and lightweight retransmission mechanism
C Wu, S Ohzahata, T Kato
IEICE transactions on communications 95 (2), 415-425, 2012
982012
Spatial intelligence toward trustworthy vehicular IoT
C Wu, Z Liu, D Zhang, T Yoshinaga, Y Ji
IEEE Communications Magazine 56 (10), 22-27, 2018
962018
A reliable energy efficient dynamic spectrum sensing for cognitive radio IoT networks
JA Ansere, G Han, H Wang, C Choi, C Wu
IEEE Internet of Things Journal 6 (4), 6748-6759, 2019
902019
Age of information aware radio resource management in vehicular networks: A proactive deep reinforcement learning perspective
X Chen, C Wu, T Chen, H Zhang, Z Liu, Y Zhang, M Bennis
IEEE Transactions on wireless communications 19 (4), 2268-2281, 2020
822020
Multi-tenant cross-slice resource orchestration: A deep reinforcement learning approach
X Chen, Z Zhao, C Wu, M Bennis, H Liu, Y Ji, H Zhang
IEEE Journal on Selected Areas in Communications 37 (10), 2377-2392, 2019
822019
A reinforcement learning-based data storage scheme for vehicular ad hoc networks
C Wu, T Yoshinaga, Y Ji, T Murase, Y Zhang
IEEE Transactions on Vehicular Technology 66 (7), 6336-6348, 2016
802016
Collaborative learning of communication routes in edge-enabled multi-access vehicular environment
C Wu, Z Liu, F Liu, T Yoshinaga, Y Ji, J Li
IEEE Transactions on Cognitive Communications and Networking 6 (4), 1155-1165, 2020
732020
Vehicular multi-access edge computing with licensed sub-6 GHz, IEEE 802.11 p and mmWave
Q Hu, C Wu, X Zhao, X Chen, Y Ji, T Yoshinaga
IEEE Access 6, 1995-2004, 2017
612017
Toward practical and intelligent routing in vehicular ad hoc networks
C Wu, Y Ji, F Liu, S Ohzahata, T Kato
IEEE Transactions on Vehicular Technology 64 (12), 5503-5519, 2015
612015
Decentralized trust evaluation in vehicular Internet of Things
S Guleng, C Wu, X Chen, X Wang, T Yoshinaga, Y Ji
IEEE Access 7, 15980-15988, 2019
582019
Distributed reinforcement learning approach for vehicular ad hoc networks
C Wu, K Kumekawa, T Kato
IEICE transactions on communications 93 (6), 1431-1442, 2010
562010
Cluster-based content distribution integrating LTE and IEEE 802.11 p with fuzzy logic and Q-learning
C Wu, T Yoshinaga, X Chen, L Zhang, Y Ji
IEEE Computational Intelligence Magazine 13 (1), 41-50, 2018
542018
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