28 citations · 35 across the 18 of their papers we have counts for
19 papers
Zero-Trust Bilateral Edge Service Trading with Deposit-Refund Regulation for Runtime Compliance
Houyi Qi, Minghui Liwang, Zhipeng Cheng +1
Privacy-sensitive edge services necessitate optimizing diverse-type resource scheduling to support trustworthy provisioning within a zero-trust security framework. However, existin…
Safe Multi-Agent Deep Reinforcement Learning for Privacy-Aware Edge-Device Collaborative DNN Inference
Hong Wang, Xuwei Fan, Zhipeng Cheng +4
As Deep Neural Network (DNN) inference becomes increasingly prevalent on edge and mobile platforms, critical challenges emerge in privacy protection, resource constraints, and dyna…
Auctioning Future Services in Edge Networks with Moving Vehicles: N-Step Look-Ahead Contracts for Sustainable Resource Provision
Ziqi Ling, Minghui Liwang, Xianbin Wang +5
Timely resource allocation in edge-assisted vehicular networks is essential for compute-intensive services such as autonomous driving and navigation. However, vehicle mobility lead…
FedAPTA: Federated Multi-task Learning for Heterogeneous Devices with Adaptive Layer-wise Pruning and Task-aware Aggregation
Zhen Yu, Yachao Yuan, Jin Wang +2
Federated Learning (FL) has shown considerable promise in Machine Learning (ML) across numerous devices for privacy protection, efficient data utilization, and dynamic collaboratio…
Privacy-Aware Joint DNN Model Deployment and Partitioning Optimization for Collaborative Edge Inference Services
Zhipeng Cheng, Xiaoyu Xia, Hong Wang +4
Edge inference (EI) has emerged as a promising paradigm to address the growing limitations of cloud-based Deep Neural Network (DNN) inference services, such as high response latenc…
Accelerating Stable Matching between Workers and Spatial-Temporal Tasks for Dynamic MCS: A Stagewise Service Trading Approach
Houyi Qi, Minghui Liwang, Xianbin Wang +4
Designing effective incentive mechanisms in mobile crowdsensing (MCS) networks is crucial for engaging distributed mobile users (workers) to contribute heterogeneous data for vario…
HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning
Xiaohong Yang, Minghui Liwang, Xianbin Wang +4
The rapid growth of AI-enabled Internet of Vehicles (IoV) calls for efficient Machine Learning (ML) solutions that can handle high vehicular mobility and decentralized data. This h…
Integrated Sensing, Communication, and Computing: An Information-oriented Resource Transaction Mechanism
Ning Chen, Zhipeng Cheng, Xuwei Fan +5
Information acquisition from target perception represents the key enabling technology of the Internet of Automatic Vehicles (IoAV), which is essential for the decision-making and c…
Towards Integrated Fine-tuning and Inference when Generative AI meets Edge Intelligence
Ning Chen, Zhipeng Cheng, Xuwei Fan +2
The high-performance generative artificial intelligence (GAI) represents the latest evolution of computational intelligence, while the blessing of future 6G networks also makes edg…
GainNet: Coordinates the Odd Couple of Generative AI and 6G Networks
Ning Chen, Jie Yang, Zhipeng Cheng +7
The rapid expansion of AI-generated content (AIGC) reflects the iteration from assistive AI towards generative AI (GAI) with creativity. Meanwhile, the 6G networks will also evolve…
QoE-oriented Dependent Task Scheduling under Multi-dimensional QoS Constraints over Distributed Networks
Xuwei Fan, Zhipeng Cheng, Ning Chen +2
Task scheduling as an effective strategy can improve application performance on computing resource-limited devices over distributed networks. However, existing evaluation mechanism…
Integrated Sensing, Communication, and Computing for Cost-effective Multimodal Federated Perception
Ning Chen, Zhipeng Cheng, Xuwei Fan +5
Federated learning (FL) is a classic paradigm of 6G edge intelligence (EI), which alleviates privacy leaks and high communication pressure caused by traditional centralized data pr…
Matching-based Hybrid Service Trading for Task Assignment over Dynamic Mobile Crowdsensing Networks
Houyi Qi, Minghui Liwang, Seyyedali Hosseinalipour +4
By opportunistically engaging mobile users (workers), mobile crowdsensing (MCS) networks have emerged as important approach to facilitate sharing of sensed/gathered data of heterog…
Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks
Minghui Liwang, Zhipeng Cheng, Wei Gong +6
The challenge of exchanging and processing of big data over mobile crowdsensing (MCS) networks calls for designing seamless data service provisioning mechanisms to enable utilizati…
Learning-Based Client Selection for Federated Learning Services Over Wireless Networks with Constrained Monetary Budgets
Zhipeng Cheng, Xuwei Fan, Minghui Liwang +2
We investigate a data quality-aware dynamic client selection problem for multiple federated learning (FL) services in a wireless network, where each client offers dynamic datasets…
Auction-Promoted Trading for Multiple Federated Learning Services in UAV-Aided Networks
Zhipeng Cheng, Minghui Liwang, Xiaoyu Xia +3
Federated learning (FL) represents a promising distributed machine learning paradigm that allows smart devices to collaboratively train a shared model via providing local data sets…
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…
Distributed Machine Learning in D2D-Enabled Heterogeneous Networks: Architectures, Performance, and Open Challenges
Zhipeng Cheng, Xuwei Fan, Minghui Liwang +3
The ever-growing concerns regarding data privacy have led to a paradigm shift in machine learning (ML) architectures from centralized to distributed approaches, giving rise to fede…
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…