Publications
2024
Yuru Zhang, Ming Zhao, Qiang Liu, Nakjung Choi, Learn to Augment Network Simulators Towards Digital Network Twins, IEEE INFOCOM Workshop NG-OPERA 2024, Vancouver, Canada, May 2024.
2023
Qiang Liu, Yongjie Xue, Yuru Zhang, Dawei Chen, Kyungtae Han, AdaMap: High-Scalable Real-Time Cooperative Perception at the Edge, the 8th ACM/IEEE Symposium on Edge Computing (SEC)
Yuru Zhang, Yongjie Xue, Qiang Liu, Nakjung Choi, Poster: Digital Network Twin via Learning-Based Simulator, IEEE International Conference on Computer Communications (INFOCOM Poster)
Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle, Inter-Cell Network Slicing with Transfer Learning Empowered Multi-Agent Deep Reinforcement Learning, IEEE Open Journal of the Communications Society
Haoxin Wang, Ziran Wang, Dawei Chen, Qiang Liu, Hongyu Ke, Kyungtae Han, Metamobility: Connecting Future Mobility With the Metaverse, IEEE Vehicular Technology Magazine.
Tianlun Hu, Qi Liao, Qiang Liu, Antonio Massaro, Georg Carle, Fast and Scalable Network Slicing by Integrating Deep Learning with Lagrangian Methods, IEEE Global Communications Conference (GLOBECOM)
Yongjie Xue, Yuru Zhang, Qiang Liu, Dawei Chen, and Kyungtae Han, CoMap: Proactive Provision for Crowdsourcing Map in Automotive Edge Computing, IEEE International Conference on Communications (ICC)
Yuru Zhang, Yongjie Xue, Qiang Liu, Nakjung Choi, and Tao Han, RoNet: Toward Robust Neural Assisted Mobile Network Configuration, IEEE International Conference on Communications (ICC)
2022
Qiang Liu, Nakjung Choi, and Tao Han, Atlas: Automate Online Service Configuration in Network Slicing, ACM 18th International Conference on emerging Networking EXperiments and Technologies (CoNEXT), 2022 [slides]
Qiang Liu, Tao Han, Jiang Linda Xie, and BaekGyu Kim, Real-Time Dynamic Map with Crowdsourcing Vehicles in Edge Computing, IEEE Transactions on Intelligent Vehicles, 2022
Qiang Liu, Nakjung Choi, and Tao Han, Deep Reinforcement Learning for End-to-End Network Slicing: Challenges and Solutions, IEEE Network Magazine, 2022
Qiang Liu, Yuru Zhang, and Haoxin Wang, EdgeMap: CrowdSourcing High Definition Map in Automotive Edge Computing, IEEE International Conference on Communications (ICC), 2022 [slides]
Tianlun Hu, Qi Liao, Qiang Liu, and Georg Carle, Network Slicing via Transfer Learning aided Distributed Deep Reinforcement Learning, IEEE Global Communications Conference (ICC), 2022
Xuehan Zhou, Ruimin Ke, Zhiyong Cui, Qiang Liu, Wenxing Qian, STFL: Spatio-temporal Federated Learning for Vehicle Trajectory Prediction, IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI), 2022
Tianlun Hu, Qi Liao, Qiang Liu, Dan Wellington, and Georg Carle, Inter-Cell Slicing Resource Partitioning via Coordinated Multi-Agent Deep Reinforcement Learning, IEEE International Conference on Communications (ICC), 2022 Best Paper Award!
Fatima Salahdine, Qiang Liu, and Tao Han, Towards Secure and Intelligent Network Slicing for 5G Networks, IEEE Open Journal of the Computer Society.
2021
Qiang Liu, Nakjung Choi, and Tao Han, OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning, ACM 17th International Conference on emerging Networking EXperiments and Technologies, (CoNEXT), 2021 [slides]
Qiang Liu, Nakjung Choi, and Tao Han, Constraint-Aware Deep Reinforcement Learning for End-to-End Resource Orchestration in Mobile Networks, IEEE 29th International Conference on Network Protocols (ICNP), 2021.
Qiang Liu, Tao Han, Jiang Linda Xie, and BaekGyu Kim, LiveMap: Real-Time Dynamic Map in Automotive Edge Computing, IEEE Conference on Computer Communications (INFOCOM), 2021.
Fatima Salahdine, Johnson Opadere, Qiang Liu, Tao Han, A survey on sleep mode techniques for ultra-dense networks in 5G and beyond, Computer Networks.
2020
Qiang Liu, Tao Han, and Nirwan Ansari, Learning-Assisted Secure End-to-End Network Slicing for Cyber-Physical Systems, IEEE Network Magazine.
Qiang Liu, Tao Han, Ning Zhang, and Ye Wang, DeepSlicing: Deep Reinforcement Learning Assisted Resource Allocation for Network Slicing, IEEE Global Communications Conference (GLOBECOM), 2020.
Qiang Liu, Tao Han, and Ephraim Moges, EdgeSlice: Slicing Wireless Edge Computing Network with Decentralized Deep Reinforcement Learning, IEEE 40th International Conference on Distributed Computing Systems (ICDCS), 2020.
2019
Qiang Liu, Tao Han, and Nirwan Ansari, Energy-Efficient On-demand Resource Provisioning in Cloud Radio Access Networks, IEEE Transactions on Green Communications and Networking.
Qiang Liu, and Tao Han, DIRECT: Distributed Cross-Domain Resource Orchestration in Cellular Edge Computing, the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing (MOBIHOC), 2019.
Qiang Liu, Tao Han, VirtualEdge: Multi-Domain Resource Orchestration and Virtualization in Cellular Edge Computing, IEEE 39th International Conference on Distributed Computing Systems (ICDCS), 2019.
Johnson Opadere, Qiang Liu, Tao Han, and Nirwan Ansari, Energy-Efficient Virtual Radio Access Networks for Multi-Operators Cooperative Cellular Networks, IEEE Transactions on Green Communications and Networking.
Johnson Opadere, Qiang Liu, Ning Zhang, and Tao Han, Joint Computation and Communication Resource Allocation for Energy-Efficient Mobile Edge Networks, IEEE International Conference on Communications, (ICC), 2019 Best Paper Award!
Qiang Liu, and Tao Han, When Network Slicing meets Deep Reinforcement Learning, In Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies Student Workshop (CoNEXT Workshop), 201.
2018
Qiang Liu, Tao Han, Nirwan Ansari, and Gang Wu, On Designing Energy-Efficient Heterogeneous Cloud Radio Access Networks, IEEE Transactions on Green Communications and Networking.
Qiang Liu, and Tao Han, DARE: Dynamic Adaptive Mobile Augmented Reality with Edge Computing, IEEE 26th International Conference on Network Protocols (ICNP), 2018.
Qiang Liu, Siqi Huang, Johnson Opadere, and Tao Han, An Edge Network Orchestrator for Mobile Augmented Reality, IEEE Conference on Computer Communications (INFOCOM), 2018.
Qiang Liu, Tao Han, and Nirwan Ansari, Energy-Efficient On-demand Cloud Radio Access Networks Virtualization, IEEE Global Communications Conference (GLOBECOM), 2018.
Qiang Liu, Tao Han, and Nirwan Ansari, Joint Radio and Computation Resource Management for Low Latency Mobile Edge Computing, IEEE Global Communications Conference (GLOBECOM), 2018.
2017
Qiang Liu, and Tao Han, Demo Abstract: Themis: Cross-Domain Resource Orchestration and Virtualization in Cellular Computing Networks, IEEE 26th International Conference on Network Protocols Demo (ICNP Demo), 2017.
Johnson Opadere, Qiang Liu, and Tao Han, Energy-Efficient RRH Sleep Mode for Virtual Radio Access Networks, IEEE Global Communications Conference (GLOBECOM), 2017.
Siqi Huang, Qiang Liu, Tao Han, Nirwan Ansari, Data-Driven Network Optimization in Ultra-Dense Radio Access Networks, IEEE Global Communications Conference (GLOBECOM), 2017.
Qiang Liu, Siqi Huang, and Tao Han, Demo Abstract: Fast and Accurate Object Analysis at the Edge for Mobile Augmented Reality, In Proceedings of the Second ACM/IEEE Symposium on Edge Computing Demo (SEC Demo), 2017.
Qiang Liu, Siqi Huang, Yang Deng, and Tao Han, Demo Abstract: MExR: Mobile Edge Resource Management for Mixed Reality Applications, IEEE Conference on Computer Communications Workshops (INFOCOM), 2017.
2016
Qiang Liu, Gang Wu, Yingchu Guo, Yusong Zhang, and Su Hu, Energy Efficient Resource Allocation for Control Data Separated Heterogeneous-CRAN, IEEE Global Communications Conference (GLOBECOM), 2016.
Qiang Liu, Tao Han, and Gang Wu, Computing Resource Aware Energy Saving Scheme for Cloud Radio Access Networks, IEEE International Conferences on Sustainable Computing and Communications, 2016.
Patents
Qiang Liu, BaekGyu Kim, Systems and methods for improving scheduling of task offloading within a vehicle, 2020
Qiang Liu, BaekGyu Kim, Rui Guo, Systems and methods to aggregate and distribute dynamic information of crowdsourcing vehicles for edge-assisted live map service, 2020
Qiang Liu, BaekGyu Kim, Systems and methods for information aggregation and event management in a vehicle, 2020