Qiang Liu

Orcid: 0000-0002-4307-2990

Affiliations:
  • University of Nebraska-Lincoln, NE, USA
  • University of North Carolina at Charlotte, Department of Electrical and Computer Engineering, NC, USA (former)


According to our database1, Qiang Liu authored at least 38 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2023
Metamobility: Connecting Future Mobility With the Metaverse.
IEEE Veh. Technol. Mag., September, 2023

Real-Time Dynamic Map With Crowdsourcing Vehicles in Edge Computing.
IEEE Trans. Intell. Veh., April, 2023

Inter-Cell Network Slicing With Transfer Learning Empowered Multi-Agent Deep Reinforcement Learning.
IEEE Open J. Commun. Soc., 2023

Deep Reinforcement Learning for End-to-End Network Slicing: Challenges and Solutions.
IEEE Netw., 2023

Poster: Digital Network Twin via Learning-Based Simulator.
Proceedings of the IEEE INFOCOM 2023, 2023

AdaMap: High-Scalable Real-Time Cooperative Perception at the Edge.
Proceedings of the IEEE/ACM Symposium on Edge Computing, 2023

RoNet: Toward Robust Neural Assisted Mobile Network Configuration.
Proceedings of the IEEE International Conference on Communications, 2023

CoMap: Proactive Provision for Crowdsourcing Map in Automotive Edge Computing.
Proceedings of the IEEE International Conference on Communications, 2023

Fast and Scalable Network Slicing by Integrating Deep Learning with Lagrangian Methods.
Proceedings of the IEEE Global Communications Conference, 2023

2022
Towards Secure and Intelligent Network Slicing for 5G Networks.
IEEE Open J. Comput. Soc., 2022

EdgeMap: CrowdSourcing High Definition Map in Automotive Edge Computing.
Proceedings of the IEEE International Conference on Communications, 2022

Inter-Cell Slicing Resource Partitioning via Coordinated Multi-Agent Deep Reinforcement Learning.
Proceedings of the IEEE International Conference on Communications, 2022

Network Slicing via Transfer Learning aided Distributed Deep Reinforcement Learning.
Proceedings of the IEEE Global Communications Conference, 2022

Atlas: automate online service configuration in network slicing.
Proceedings of the 18th International Conference on emerging Networking EXperiments and Technologies, 2022

2021
A survey on sleep mode techniques for ultra-dense networks in 5G and beyond.
Comput. Networks, 2021

LiveMap: Real-Time Dynamic Map in Automotive Edge Computing.
Proceedings of the 40th IEEE Conference on Computer Communications, 2021

Constraint-Aware Deep Reinforcement Learning for End-to-End Resource Orchestration in Mobile Networks.
Proceedings of the 29th IEEE International Conference on Network Protocols, 2021

OnSlicing: online end-to-end network slicing with reinforcement learning.
Proceedings of the CoNEXT '21: The 17th International Conference on emerging Networking EXperiments and Technologies, Virtual Event, Munich, Germany, December 7, 2021

2020
Learning-Assisted Secure End-to-End Network Slicing for Cyber-Physical Systems.
IEEE Netw., 2020

EdgeSlice: Slicing Wireless Edge Computing Network with Decentralized Deep Reinforcement Learning.
Proceedings of the 40th IEEE International Conference on Distributed Computing Systems, 2020

DeepSlicing: Deep Reinforcement Learning Assisted Resource Allocation for Network Slicing.
Proceedings of the IEEE Global Communications Conference, 2020

2019
Energy-Efficient Virtual Radio Access Networks for Multi-Operators Cooperative Cellular Networks.
IEEE Trans. Green Commun. Netw., 2019

Energy-Efficient On-Demand Resource Provisioning in Cloud Radio Access Networks.
IEEE Trans. Green Commun. Netw., 2019

DIRECT: Distributed Cross-Domain Resource Orchestration in Cellular Edge Computing.
Proceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2019

VirtualEdge: Multi-Domain Resource Orchestration and Virtualization in Cellular Edge Computing.
Proceedings of the 39th IEEE International Conference on Distributed Computing Systems, 2019

Joint Computation and Communication Resource Allocation for Energy-Efficient Mobile Edge Networks.
Proceedings of the 2019 IEEE International Conference on Communications, 2019

When Network Slicing meets Deep Reinforcement Learning.
Proceedings of the 15th International Conference on emerging Networking EXperiments and Technologies, 2019

2018
On Designing Energy-Efficient Heterogeneous Cloud Radio Access Networks.
IEEE Trans. Green Commun. Netw., 2018

An Edge Network Orchestrator for Mobile Augmented Reality.
Proceedings of the 2018 IEEE Conference on Computer Communications, 2018

Demo Abstract: Themis: Cross-Domain Resource Orchestration and Virtualization in Cellular Computing Networks.
Proceedings of the 2018 IEEE 26th International Conference on Network Protocols, 2018

DARE: Dynamic Adaptive Mobile Augmented Reality with Edge Computing.
Proceedings of the 2018 IEEE 26th International Conference on Network Protocols, 2018

Energy-Efficient On-Demand Cloud Radio Access Networks Virtualization.
Proceedings of the IEEE Global Communications Conference, 2018

Joint Radio and Computation Resource Management for Low Latency Mobile Edge Computing.
Proceedings of the IEEE Global Communications Conference, 2018

2017
Demo abstract: MExR: Mobile edge resource management for mixed reality applications.
Proceedings of the 2017 IEEE Conference on Computer Communications Workshops, 2017

Energy-Efficient RRH Sleep Mode for Virtual Radio Access Networks.
Proceedings of the 2017 IEEE Global Communications Conference, 2017

Data-Driven Network Optimization in Ultra-Dense Radio Access Networks.
Proceedings of the 2017 IEEE Global Communications Conference, 2017

Fast and accurate object analysis at the edge for mobile augmented reality: demo.
Proceedings of the Second ACM/IEEE Symposium on Edge Computing, San Jose / Silicon Valley, 2017

2016
Computing Resource Aware Energy Saving Scheme for Cloud Radio Access Networks.
Proceedings of the 2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), 2016


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