Dr. Juan Zhang

Dr. Juan Zhang

Lecturer

Posts by Collection

portfolio

publications

QoE-Aware and Energy-Efficient Transmission of Multimedia Traffic in Wireless Networks

Published in International Conference on Sensor Networks and Signal Processing (SNSP), 2018

This paper discusses the existing approaches for achieving QoE-aware and energy efficient video transmission from different perspectives such as resource allocation, traffic buffering and other scheduling strategies.

Recommended citation: J. Zhang, Y. Chen, H. Zhang and F. Zhang, "QoE-Aware and Energy-Efficient Transmission of Multimedia Traffic in Wireless Networks," 2018 International Conference on Sensor Networks and Signal Processing (SNSP), 2018, pp. 152-157, doi: 10.1109/SNSP.2018.00036. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8615914

Real-time urban regional route planning model for connected vehicles based on V2X communication

Published in Journal of Transport and Land Use, 2020

To improve the capacity of urban transport and optimize land-use planning, a novel real-time regional route planning model based on vehicle to X communication (V2X) is presented in this paper.

Recommended citation: Wang, Pangwei, et al. “Real-Time Urban Regional Route Planning Model for Connected Vehicles Based on V2X Communication.” Journal of Transport and Land Use, vol. 13, no. 1, 2020, pp. 517–38. JSTOR, https://www.jstor.org/stable/26967257. Accessed 3 Jul. 2022. https://www.jstor.org/stable/10.2307/26967257

Balancing energy consumption and reputation gain of UAV scheduling in edge computing

Published in IEEE Transactions on Cognitive Communications and Networking, 2020

In this paper, we clarify the issue on how to maintain the energy efficiency of UAVs and guarantee the reputation gain during the scheduling deployment.

Recommended citation: J. Zhang, Y. Wu, G. Min, F. Hao and L. Cui, "Balancing Energy Consumption and Reputation Gain of UAV Scheduling in Edge Computing," in IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 4, pp. 1204-1217, Dec. 2020, doi: 10.1109/TCCN.2020.3004592. https://ieeexplore.ieee.org/abstract/document/9124670

Multilane Spatiotemporal Trajectory Optimization Method (MSTTOM) for Connected Vehicles

Published in Journal of Advanced Transportation, 2020

This paper proposes a multilane spatiotemporal trajectory optimization method (MSTTOM) to reach full potential of connected vehicles by considering vehicular safety, traffic capacity, fuel efficiency, and driver comfort.

Recommended citation: Pangwei Wang, Yunfeng Wang, Hui Deng, Mingfang Zhang, Juan Zhang, "Multilane Spatiotemporal Trajectory Optimization Method (MSTTOM) for Connected Vehicles", Journal of Advanced Transportation, vol. 2020, Article ID 8819911, 15 pages, 2020. https://doi.org/10.1155/2020/8819911 https://www.hindawi.com/journals/jat/2020/8819911/

Model predictive control for connected vehicle platoon under switching communication topology

Published in IEEE Transactions on Intelligent Transportation Systems, 2021

In this work, a distributed model predictive control (MPC) algorithm is proposed for connected vehicle platoon with a focus on switching communication topologies and control strategy under abnormal communications.

Recommended citation: Wang, P., Deng, H., Zhang, J., Wang, L., Zhang, M., & Li, Y. (2021). Model predictive control for connected vehicle platoon under switching communication topology. IEEE Transactions on Intelligent Transportation Systems. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9418551

An Intelligent Actuator of an Indoor Logistics System Based on Multi-Sensor Fusion

Published in Actuators, 2021

In order to achieve better logistics distribution efficiency, this paper proposes an intelligent actuator of an indoor logistics system by fusing multiple involved sensors.

Recommended citation: Wang, P.; Wang, Y.; Wang, X.; Liu, Y.; Zhang, J. An Intelligent Actuator of an Indoor Logistics System Based on Multi-Sensor Fusion. Actuators 2021, 10, 120. https://doi.org/10.3390/act10060120 https://www.mdpi.com/2076-0825/10/6/120

System revenue maximization for offloading decisions in mobile edge computing

Published in ICC, 2021

This paper studies the revenue maximization of network operators through a pricing scheme in mobile edge computing, by explicitly formulating energy consumption and latency into the offloading strategy.

Recommended citation: J. Zhang, Y. Wu and G. Min, "System Revenue Maximization for Offloading Decisions in Mobile Edge Computing," ICC 2021 - IEEE International Conference on Communications, 2021, pp. 1-6, doi: 10.1109/ICC42927.2021.9500485. https://ieeexplore.ieee.org/abstract/document/9500485

Short-Term Traffic State Prediction Based on Mobile Edge Computing in V2X Communication

Published in Applied Science, 2021

In this paper, a short-term traffic prediction model based on complex neural network is proposed under the environment of vehicle-to-everything (V2X) communication systems.

Recommended citation: Wang,P.;Liu,X.;Wang,Y.; Wang, T.; Zhang, J. Short-Term Traffic State Prediction Based on Mobile Edge Computing in V2X Communication. Appl. Sci. 2021, 11, 11530. https://doi.org/10.3390/app112311530

talks

teaching

Formal Methods

Workshop, Beihang University, School of Reliability and Systems Engineering, 2011

ECMM445: Learning from Data

Workshop, University of Exeter, Department of Computer Science. Summer, 2021

60hrs workshop for master students.