45 citations · 64 across the 14 of their papers we have counts for
15 papers
A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach for UAV-Assisted Vehicular Networks with Delayed CSI Feedback
Zhang Liu, Lianfen Huang, Zhibin Gao +4
Low altitude uncrewed aerial vehicles (UAVs) are expected to facilitate the development of aerial-ground integrated intelligent transportation systems and unlocking the potential o…
Generative AI for Lyapunov Optimization Theory in UAV-based Low-Altitude Economy Networking
Zhang Liu, Dusit Niyato, Jiacheng Wang +4
Lyapunov optimization theory has recently emerged as a powerful mathematical framework for solving complex stochastic optimization problems by transforming long-term objectives int…
Joint Model Caching and Resource Allocation in Generative AI-Enabled Wireless Edge Networks
Zhang Liu, Hongyang Du, Lianfen Huang +2
With the rapid advancement of artificial intelligence (AI), generative AI (GenAI) has emerged as a transformative tool, enabling customized and personalized AI-generated content (A…
DNN Partitioning, Task Offloading, and Resource Allocation in Dynamic Vehicular Networks: A Lyapunov-Guided Diffusion-Based Reinforcement Learning Approach
Zhang Liu, Hongyang Du, Junzhe Lin +4
The rapid advancement of Artificial Intelligence (AI) has introduced Deep Neural Network (DNN)-based tasks to the ecosystem of vehicular networks. These tasks are often computation…
GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds
Zhang Liu, Lianfen Huang, Zhibin Gao +3
Vehicular clouds (VCs) are modern platforms for processing of computation-intensive tasks over vehicles. Such tasks are often represented as directed acyclic graphs (DAGs) consisti…
RFID: Towards Low Latency and Reliable DAG Task Scheduling over Dynamic Vehicular Clouds
Zhang Liu, Minghui Liwang, Seyyedali Hosseinalipour +3
Vehicular cloud (VC) platforms integrate heterogeneous and distributed resources of moving vehicles to offer timely and cost-effective computing services. However, the dynamic natu…
Long-Term or Temporary? Hybrid Worker Recruitment for Mobile Crowd Sensing and Computing
Minghui Liwang, Zhibin Gao, Seyyedali Hosseinalipour +3
This paper investigates a novel hybrid worker recruitment problem where the mobile crowd sensing and computing (MCSC) platform employs workers to serve MCSC tasks with diverse qual…
Let' s Trade in The Future! A Futures-Enabled Fast Resource Trading Mechanism in Edge Computing-Assisted UAV Networks
Minghui Liwang, Zhibin Gao, Xianbin Wang
Mobile edge computing (MEC) has emerged as one of the key technical aspects of the fifth-generation (5G) networks. The integration of MEC with resource-constrained unmanned aerial…
Energy-Aware Graph Task Scheduling in Software-Defined Air-Ground Integrated Vehicular Networks
Minghui LiWang, Zhibin Gao, Xianbin Wang
The Software-Defined Air-Ground integrated Vehicular (SD-AGV) networks have emerged as a promising paradigm, which realize the flexible on-ground resource sharing to support innova…
Learning-Based Joint User-AP Association and Resource Allocation in Ultra Dense Network
Zhipeng Cheng, Minghui LiWangy, Ning Chen +3
With the advantages of Millimeter wave in wireless communication network, the coverage radius and inter-site distance can be further reduced, the ultra dense network (UDN) becomes…
A Truthful Auction for Graph Job Allocation in Vehicular Cloud-assisted Networks
Zhibin Gao, Minghui LiWang, Seyyedali Hosseinalipour +2
Vehicular cloud computing has emerged as a promising solution to fulfill users' demands on processing computation-intensive applications in modern driving environments. Such applic…
Energy-aware Allocation of Graph Jobs in Vehicular Cloud Computing-enabled Software-defined IoV
Minghui LiWang, Zhibin Gao, Seyyedali Hosseinalipour +2
Software-defined internet of vehicles (SDIoV) has emerged as a promising paradigm to realize flexible and comprehensive resource management, for next generation automobile transpor…
Multi-Task Offloading over Vehicular Clouds under Graph-based Representation
Minghui Liwang, Zhibin Gao, Seyyedali Hosseinalipour +1
Vehicular cloud computing has emerged as a promising paradigm for realizing user requirements in computation-intensive tasks in modern driving environments. In this paper, a novel…
Allocation of Computation-Intensive Graph Jobs over Vehicular Clouds in IoV
Minghui LiWang, Seyyedali Hosseinalipour, Zhibin Gao +3
Graph jobs represent a wide variety of computation-intensive tasks in which computations are represented by graphs consisting of components (denoting either data sources or data pr…
A Computation Offloading Incentive Mechanism with Delay and Cost Constraints under 5G Satellite-ground IoV architecture
Minghui LiWang, Shijie Dai, Zhibin Gao +3
The 5G Internet of Vehicles has become a new paradigm alongside the growing popularity and variety of computation-intensive applications with high requirements for computational re…