By year
Copyright Notice
Age-Optimal Scheduling for Heterogeneous Traffic with Timely-Throughput Constraint
Tuo Liu, Sheng Zhou, Zhisheng Niu, Joint Optimization of Cache Allocation and Content Placement in Urban Vehicular Networks, IEEE GLOBECOM 2018, Abu Dhabi, Dec. 9-13，2018
Error Analysis for Status Update From Sensors With Temporally and Spatially Correlated Observations
H. Zhang, Z. Jiang, S. Xu and S. Zhou, Error Analysis for Status Update From Sensors With Temporally and Spatially Correlated Observations, IEEE Transactions on Wireless Communications, 2021, 20(3): 2136-2149.
Distributed Task Replication for Vehicular Edge Computing: Performance Analysis and Learning-Based Algorithm
Y. Sun, S. Zhou and Z. Niu, Distributed Task Replication for Vehicular Edge Computing: Performance Analysis and Learning-Based Algorithm, IEEE Transactions on Wireless Communications, 2021, 20(2):1138-1151.
Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning
W. Shi, S. Zhou, Z. Niu, M. Jiang and L. Geng, Joint Device Scheduling and Resource Allocation for Latency Constrained Wireless Federated Learning, IEEE Transactions on Wireless Communications, 2021, 20(1):453-467.
Achieving Cooperative Diversity in Over-the-Air Computation via Relay Selection
R. Jiang, S. Zhou and K. Huang, Achieving Cooperative Diversity in Over-the-Air Computation via Relay Selection, 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), 2020.
Edge Learning with Timeliness Constraints: Challenges and Solutions
Y. Sun, W. Shi, X. Huang, S. Zhou and Z. Niu, Edge Learning with Timeliness Constraints: Challenges and Solutions, IEEE Communications Magazine, 2020, 58(12):27-33.
Timely Status Update Based on Urgency of Information with Statistical Context
L. Wang, J. Sun, S. Zhou and Z. Niu, Timely Status Update Based on Urgency of Information with Statistical Context, 2020 32nd International Teletraffic Congress (ITC 32), 2020.
Urgency of Information for Context-Aware Timely Status Updates in Remote Control Systems
X. Zheng, S. Zhou, and Z. Niu, Urgency of Information for Context-Aware Timely Status Updates in Remote Control Systems, IEEE Trans. Wireless Commun. accepted.
Dynamic Compression Ratio Selection for Edge Inference Systems with Hard Deadlines
X. Huang and S. Zhou, Dynamic Compression Ratio Selection for Edge Inference Systems with Hard Deadlines, IEEE Internet of Things J., accepted.
Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning
R. Jiang and S. Zhou, Cluster-Based Cooperative Digital Over-the-Air Aggregation for Wireless Federated Edge Learning, 2020 IEEE/CIC International Conference on Communications in China (ICCC), 2020.
Age-Optimal Scheduling for Heterogeneous Traffic with Timely-Throughput Constraint
J. Sun, Z. Jiang, S. Zhou, and Z. Niu, Age-Optimal Scheduling for Heterogeneous Traffic with Timely-Throughput Constraint, IEEE INFOCOM’20 AoI Workshop, July 2020.
SENATE: A Permissionless Byzantine Consensus Protocol in Wireless Networks for Real-Time Internet-of-Things Applications
Z. Jiang, Z. Cao, B. Krishnamachari, S. Zhou, and Z. Niu, SENATE: A Permissionless Byzantine Consensus Protocol in Wireless Networks for Real-Time Internet-of-Things Applications, IEEE Internet of Things J., 2020, 7(7):6576-6588.
SFC-Based Service Provisioning for Reconfigurable Space-Air-Ground Integrated Networks
G. Wang, S. Zhou, S. Zhang, Z. Niu, and S. Shen, SFC-Based Service Provisioning for Reconfigurable Space-Air-Ground Integrated Networks, IEEE J. Sel. Areas Commun., 2020, 38(7):1478-1489.
Adaptive Transmission for Edge Learning via Training Loss Estimation
X. Huang and S. Zhou, Adaptive Transmission for Edge Learning via Training Loss Estimation, IEEE ICC’20, Jun. 2020.
Energy-Aware Analog Aggregation for Federated Learning with Redundant Data
Y. Sun, S. Zhou, and D. Gunduz, Energy-Aware Analog Aggregation for Federated Learning with Redundant Data, IEEE ICC’20, Jun. 2020.
Device Scheduling with Fast Convergence for Wireless Federated Learning
W. Shi, S. Zhou, and Z. Niu, Device Scheduling with Fast Convergence for Wireless Federated Learning, IEEE ICC’20, Jun. 2020.
Latency Guaranteed Edge Inference via Dynamic Compression Ratio Selection
X. Huang and S. Zhou, Latency Guaranteed Edge Inference via Dynamic Compression Ratio Selection, IEEE WCNC’20, May 2020.
Energy-optimal and delay-bounded computation offloading in mobile edge computing with heterogeneous clouds
T. Zhao, S. Zhou, L. Song, Z. Jiang, X. Guo, and Z. Niu, Energy-optimal and delay-bounded computation offloading in mobile edge computing with heterogeneous clouds, China Communications, 2020, 17(5):191-210.
Fractional Dynamic Caching: A Collaborative Design of Storage and Backhaul
L. Wang and S. Zhou, Fractional Dynamic Caching: A Collaborative Design of Storage and Backhaul, IEEE Trans. Veh. Technol., 2020, 69(4):4194-4206.
A Deep Reinforcement Learning Framework to Combat Dynamic Blockage in mmWave V2X Networks
S. Chen, K. Vu, S. Zhou, Z. Niu, M. Bennis, M. Latva-aho, A Deep Reinforcement Learning Framework to Combat Dynamic Blockage in mmWave V2X Networks, 6G Summit 2020, Mar. 2020.