Publications

We present some interesting studies. You can find my all articles on my Google Scholar profile.

From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks

Published in IEEE Internet of Things Magazine, 2024

In this article, we present the concept of GIoT and conduct an exploration of its potential prospects.

Recommended citation: Jinbo Wen, Jiangtian Nie, Jiawen Kang, Dusit Niyato, Hongyang Du, Yang Zhang, and Mohsen Guizani, "From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks," IEEE Internet of Things Magazine, pp. 30-37, May 2024. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10517486

Optimizing Information Propagation for Blockchain-empowered Mobile AIGC: A Graph Attention Network Approach

Published in IWCMC 2024-The 20th International Wireless Communications & Mobile Computing Conference, 2024

In this paper, we design a Graph Attention Network (GAT)-based information propagation optimization framework for blockchain-empowered mobile AIGC.

Recommended citation: Jiana Liao, Jinbo Wen, Jiawen Kang, Yang Zhang, Jianbo Du, Qihao Li, Weiting Zhang, Dong Yang, "Optimizing Information Propagation for Blockchain-empowered Mobile AIGC: A Graph Attention Network Approach," IWCMC 2024-The 20th International Wireless Communications & Mobile Computing Conference, arXiv preprint arXiv:2404.04937, 2024. https://arxiv.org/pdf/2404.04937

Task Freshness-aware Incentive Mechanism for Vehicle Twin Migration in Vehicular Metaverses

Published in MetaCom-2023 IEEE International Conference on Metaverse Computing, Networking and Applications, 2023

In this paper, we design an efficient incentive mechanism framework for VT migrations. We first propose a novel metric named Age of Migration Task (AoMT) to quantify the task freshness of the VT migration. AoMT measures the time elapsed from the first collected sensing data of the freshest avatar migration task to the last successfully processed data at the next RSU. To incentivize the contribution of bandwidth resources among the next RSUs, we propose an AoMT-based contract model, where the optimal contract is derived to maximize the expected utility of the RSU that provides metaverse services.

Recommended citation: Jinbo Wen, Jiawen Kang, Zehui Xiong, Yang Zhang, Hongyang Du, Yutao Jiao, Dusit Niyato, "Task freshness-aware incentive mechanism for vehicle twin migration in vehicular metaverses," MetaCom-2023 IEEE International Conference on Metaverse Computing, Networking and Applications, Oct 2023. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10271832

Blockchain-empowered Federated Learning for Healthcare Metaverses User-centric Incentive Mechanism with Optimal Data Freshness

Published in IEEE Transactions on Cognitive Communications and Networking, 2023

In this paper, we first design a user-centric privacy-preserving framework based on decentralized Federated Learning (FL) for healthcare metaverses. To further improve the privacy protection of healthcare metaverses, a cross-chain empowered FL framework is utilized to enhance sensing data security. This framework utilizes a hierarchical cross-chain architecture with a main chain and multiple subchains to perform decentralized, privacy-preserving, and secure data training in both virtual and physical spaces. Moreover, we utilize Age of Information (AoI) as an effective data-freshness metric and propose an AoI-based contract theory model under Prospect Theory (PT) to motivate sensing data sharing in a user-centric manner. This model exploits PT to better capture the subjective utility of the service provider.

Recommended citation: Jiawen Kang, Jinbo Wen, Dongdong Ye, Bingkun Lai, Tianhao Wu, Zehui Xiong, Jiangtian Nie, Dusit Niyato, Yang Zhang, and Shengli Xie, "Blockchain-empowered federated learning for healthcare Metaverses: User-centric incentive mechanism with optimal data freshness," IEEE Transactions on Cognitive Communications and Networking, pp. 348-362, Feb 2024. https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10254627

Freshness-aware Incentive Mechanism for Mobile AI-Generated Content (AIGC) Networks

Published in ICCC-2023 IEEE/CIC International Conference on Communications in China, 2023

In this paper, we first utilize Age of Information (AoI) as a well-accepted data-freshness metric to quantify data freshness for AIGC fine-tuning. Then, we propose an AoI-based contract theory model to incentivize the contribution of fresh data among UAVs. Moreover, we design the optimal contract that is feasible to maximize the expected utility of the base station that is responsible for dispatching UAVs to collaboratively perform AIGC tasks.

Recommended citation: Jinbo Wen, Jiawen Kang, Minrui Xu, Hongyang Du, Zehui Xiong, Yang Zhang, Dusit Niyato, "Freshness-aware incentive mechanism for mobile AI-Generated Content (AIGC) networks," ICCC-2023 IEEE/CIC International Conference on Communications in China, Sep 2023. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=10233667