A Learning-Based Incentive Mechanism for Federated Learning

Human-level control through deep reinforcement learning

Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., Graves, A., Riedmiller, M., Fidjeland, A. K., Ostrovski, G., et al. (2015) · Nature · doi:10.1038/nature14236 · Cited by 30,357

Reinforcement Learning: An Introduction

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Communication-Efficient Learning of Deep Networks from Decentralized Data

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Proximal Policy Optimization Algorithms

Schulman, J., Wolski, F., Dhariwal, P., Radford, A., & Klimov, O. (2017) · arXiv · doi:10.48550/arxiv.1707.06347 · Cited by 10,625

Reinforcement Learning: An Introduction

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Trust region policy optimization

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Real-time status: How often should one update?

Kaul, S. K., Yates, R. D., & Gruteser, M. (2012) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infcom.2012.6195689 · Cited by 2,508

Actor-critic algorithms

Konda, V. R., & Tsitsiklis, J. N. (2002) · Cited by 2,202

Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing

Li, H., Ota, K., & Dong, M. (2018) · IEEE Network · doi:10.1109/mnet.2018.1700202 · Cited by 1,566

Interpreting Usability Factors Predicting Sustainable Adoption of Cloud-Based E-Learning Environment during COVID-19 Pandemic

Dutta, B., Peng, M.-H., Chen, C.-C., & Sun, S.-L. (2021) · Sustainability · doi:10.3390/su13169329 · Cited by 21

A Blockchain-Based Privacy Information Security Sharing Scheme in Industrial Internet of Things

Wang, Y., Che, T., Zhao, X., Zhou, T., Zhang, K., & Hu, X. (2022) · Sensors · doi:10.3390/s22093426 · Cited by 20

Joint Participation Incentive and Network Pricing Design for Federated Learning

Ding, N., Gao, L. X., & Huang, J. (2023) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom53939.2023.10229084 · Cited by 21

CSRA: Robust Incentive Mechanism Design for Differentially Private Federated Learning

Yang, Y., Hu, M., Zhou, Y., Liu, X., & Wu, D. (2023) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2023.3329441 · Cited by 21

EPViSA: Efficient Auction Design for Real-Time Physical-Virtual Synchronization in the Human-Centric Metaverse

Xu, M., Niyato, D. T., Wright, B., Zhang, H., Kang, J., Xiong, Z., Mao, S., & Han, Z. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3345383 · Cited by 20

Federated Learning Incentive Mechanism Design via Enhanced Shapley Value Method

Yang, X., Tan, W., Peng, C., Xiang, S., & Niu, K. (2022) · Wireless Communications and Mobile Computing · doi:10.1155/2022/9690657 · Cited by 19

MarS-FL: Enabling Competitors to Collaborate in Federated Learning

Wu, X., & Yu, H. (2022) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2022.3186991 · Cited by 19

Eliminating Communication Bottlenecks in Cross-Device Federated Learning with In-Network Processing at the Edge

Luo, S., Fan, P., Xing, H., Luo, L., & Yu, H. (2022) · International Conference on Communications · doi:10.1109/icc45855.2022.9838381 · Cited by 19

HSFL: An Efficient Split Federated Learning Framework via Hierarchical Organization

Xia, T., Deng, Y., Yue, S., He, J., Ren, J., & Zhang, Y. (2022) · International Conference on Network and Service Management (CNSM) · doi:10.23919/cnsm55787.2022.9964646 · Cited by 19

A hierarchical federated learning incentive mechanism in UAV-assisted edge computing environment

He, G., Li, C., Song, M., Shu, Y., Chengwei, L., & Luo, Y. (2023) · Ad Hoc Networks · doi:10.1016/j.adhoc.2023.103249 · Cited by 19

Energy-Aware Incentive Mechanism for Hierarchical Federated Learning Using Water Filling Technique

Cui, Y., Tong, W., Liu, T., Cao, K., Zhou, J., Xu, M., & Wei, T. (2024) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2024.3441659 · Cited by 19

Nothing Wasted: Full Contribution Enforcement in Federated Edge Learning

Hu, Q., Wang, S., Xiong, Z., & Cheng, X. (2021) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2021.3123195 · Cited by 18

BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning

Xing, P., Lu, S., Wu, L., & Yu, H. (2022) · IEEE Transactions on Big Data · doi:10.1109/tbdata.2022.3191439 · Cited by 21

Reliable incentive mechanism in hierarchical federated learning based on two-way reputation and contract theory

Cai, H., Gao, L., Wang, J., & Li, F. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.05.045 · Cited by 18

Measurement and Applications: Exploring the Challenges and Opportunities of Hierarchical Federated Learning in Sensor Applications

Ooi, M. P., Sohail, S., Huang, V., Hudson, N., Baughman, M., RANA, O. F., Hinze, A., Chard, K., Chard, R., Foster, I. T., et al. (2023) · IEEE Instrumentation & Measurement Magazine · doi:10.1109/mim.2023.10328671 · Cited by 20

An Incentive Mechanism for Federated Learning: A Continuous Zero-Determinant Strategy Approach

Tang, C., Yang, B., Xie, X., Chen, G., Al‐qaness, M. A. A., & Liu, Y. (2024) · IEEE/CAA Journal of Automatica Sinica · doi:10.1109/jas.2023.123828 · Cited by 17

PR-OppCL: Privacy-Preserving Reputation-Based Opportunistic Federated Learning in Intelligent Transportation System

Li, Q., Yi, X., Nie, J., & Zhu, Y. (2024) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2024.3375298 · Cited by 17

Game-Theoretic Design of Quality-Aware Incentive Mechanisms for Hierarchical Federated Learning

Hu, G., Han, J., Lu, J., Yu, J., Qiu, S., Peng, H., Zhu, D., & Li, T. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3394170 · Cited by 18

Auction-based client selection for online Federated Learning

Guo, J., Li-na, S., Liu, J., Ding, J., Liu, X., Huang, B., & Li, L. (2024) · Information Fusion · doi:10.1016/j.inffus.2024.102549 · Cited by 19

Federated Learning: A Survey of a New Approach to Machine Learning

Hussain, G. K. J., & Manoj, G. (2022) · International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) · doi:10.1109/iceeict53079.2022.9768446 · Cited by 17

Blockchain-Based Medical Data Asset Sharing Framework for Healthcare 4.0

Li, M., Harish, A. R., Yu, C., Yu, Y. J., Zhong, R. Y., & Huang, G. Q. (2025) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2024.3488795 · Cited by 16

Incentive-Aware Decentralized Data Collaboration

Wang, Y., Wu, Y., Chen, X., Feng, G., & Ooi, B. C. (2023) · Proceedings of the ACM on Management of Data · doi:10.1145/3589303 · Cited by 16

Incentivization and Aggregation Schemes for Federated Learning Applications

Hassija, V., Chawla, V., Chamola, V., & Sikdar, B. (2023) · IEEE Transactions on Machine Learning in Communications and Networking · doi:10.1109/tmlcn.2023.3302811 · Cited by 16

Incentive mechanism design for Federated Learning with Stackelberg game perspective in the industrial scenario

Guo, W., Wang, Y., & Jiang, P. (2023) · Computers & Industrial Engineering · doi:10.1016/j.cie.2023.109592 · Cited by 16

Incentive-Aware Resource Allocation for Multiple Model Owners in Federated Learning

Chen, F.-Y., & Yen, L. (2024) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2024.3376259 · Cited by 16

A federated learning model for integrating sustainable routing with the Internet of Vehicular Things using genetic algorithm

Khatua, S., De, D., Maji, S., Maity, S., & Nielsen, I. E. (2024) · Decision Analytics Journal · doi:10.1016/j.dajour.2024.100486 · Cited by 18

Two-Stage Client Selection for Federated Learning Against Free-Riding Attack: A Multiarmed Bandits and Auction-Based Approach

Lu, R., Zhang, W., He, H. X., Li, Q., Zhong, X., Yang, H., Wang, D., Shi, L., Guo, Y., & Wang, Z. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3431555 · Cited by 16

Multidisciplinary cancer disease classification using adaptive FL in healthcare industry 5.0

Abbas, T., Fatima, A., Shahzad, T., Alharbi, M., Khan, M. A., & Ahmed, A. (2024) · Scientific Reports · doi:10.1038/s41598-024-68919-1 · Cited by 20

Incentive Framework for Cross-Device Federated Learning and Analytics With Multiple Tasks Based on a Multi-Leader-Follower Game

Yu, Y., Chen, D., Tang, X., Song, T., Hong, C. S., & Han, Z. (2022) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2022.3190377 · Cited by 16

Truthful Incentive Mechanism Design via Internalizing Externalities and LP Relaxation for Vertical Federated Learning

Lu, J., Pan, B., Seid, A. M., Li, B., Hu, G., & Wan, S. (2022) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3227270 · Cited by 17

FedCCEA : A Practical Approach of Client Contribution Evaluation for Federated LearningPreprint

Shyn, S. K., Kim, D.-H., & Kim, K. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.02310 · Cited by 33

An Incentive Mechanism for Big Data Trading in End-Edge-Cloud Hierarchical Federated Learning

Zhao, Y., Liu, Z., Qiu, C., Wang, X., Yu, F. R., & Leung, V. C. M. (2021) · Globecom · doi:10.1109/globecom46510.2021.9685514 · Cited by 15

From Eye to Brain: A Proactive and Distributed Crowdsensing Framework for Federated Learning

Wu, H., Zeng, H. Y., Zhou, T., Cai, Z., Xiong, Z., Niyato, D. T., & Han, Z. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3230050 · Cited by 15

A Novel Blockchain-Assisted Aggregation Scheme for Federated Learning in IoT Networks

Liu, Z., Zheng, K., Hou, L., Yang, H., & Yang, K. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3277463 · Cited by 15

Joint Device Participation, Dataset Management, and Resource Allocation in Wireless Federated Learning via Deep Reinforcement Learning

Chen, J., Zhang, J., Zhao, N., Pei, Y., Liang, Y., & Niyato, D. T. (2023) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2023.3325843 · Cited by 15

Learning-based Incentive Mechanism for Task Freshness-aware Vehicular Twin Migration

Zhang, J., Nie, J., Wen, J., Kang, J., Xu, M., Luo, X., & Niyato, D. T. (2023) · IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW) · doi:10.1109/icdcsw60045.2023.00020 · Cited by 15

Optimal Mechanism Design for Heterogeneous Client Sampling in Federated Learning

Liao, G., Luo, B., Feng, Y., Zhang, M., & Chen, X. (2024) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2024.3379659 · Cited by 17

A Game-theoretic Framework for Privacy-preserving Federated Learning

Zhang, X., Fan, L., Wang, S., Li, W., Chen, K., & Yang, Q. (2024) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3656049 · Cited by 21

Impact of Personality Traits and Information Privacy Concern on E-Learning Environment Adoption during COVID-19 Pandemic: An Empirical Investigation

Peng, M.-H., & Dutta, B. (2022) · Sustainability · doi:10.3390/su14138031 · Cited by 17

Efficiency-Boosting Federated Learning in Wireless Networks: A Long-Term Perspective

Ji, Y., Zhong, X., Kou, Z., Zhang, S., Li, H., & Yang, Y. (2023) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2023.3250273 · Cited by 15

Blockchain-Based Participant Selection for Federated Learning

Zhang, K., Huang, H., Guo, S., & Zhou, X. (2020) · Communications in computer and information science · doi:10.1007/978-981-15-9213-3_9 · Cited by 15

Federated Imitation Learning: A Cross-Domain Knowledge Sharing Framework for Traffic Scheduling in 6G Ubiquitous IoT

Yu, A., Yang, Q., Dou, L., & Cheriet, M. (2021) · IEEE Network · doi:10.1109/mnet.011.2100134 · Cited by 14

Efficient Distributed DNNs in the Mobile-Edge-Cloud Continuum

Malandrino, F., Chiasserini, C. F., & di Giacomo, G. (2022) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2022.3222640 · Cited by 15

Acceptance of Location-Based Advertising by Young Consumers: A Stimulus-Organism-Response (S-O-R) Model Perspective

Kini, R. B., Bolar, K. P., Rofin, T. M., Mukherjee, S., & Bhattacharjee, S. (2023) · Information Systems Management · doi:10.1080/10580530.2023.2214843 · Cited by 16

Federated Learning Incentive Mechanism Design via Shapley Value and Pareto Optimality

Yang, X., Xiang, S., Peng, C., Tan, W., Li, Z., Wu, N., & Zhou, Y. (2023) · Axioms · doi:10.3390/axioms12070636 · Cited by 14

Stochastic Coded Federated Learning: Theoretical Analysis and Incentive Mechanism Design

Sun, Y., Shao, J., Mao, Y., Li, S., & Zhang, J. (2023) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2023.3334732 · Cited by 16

A Practical Federated Learning Framework With Truthful Incentive in UAV-Assisted Crowdsensing

Xie, L., Su, Z., Wang, Y., & Li, Z. (2024) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2024.3484946 · Cited by 17

Decentralized Federated Learning for Private Smart Healthcare: A Survey

Cheng, H., Qu, Y., Liu, W., Gao, L., & Zhu, T. (2025) · Mathematics · doi:10.3390/math13081296 · Cited by 14

Utility Fairness for the Differentially Private Federated-Learning-Based Wireless IoT Networks

Alvi, S. A., Hong, Y., & Durrani, S. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3165596 · Cited by 17

A D2D-Aided Federated Learning Scheme With Incentive Mechanism in 6G Networks

Fantacci, R., & Picano, B. (2022) · IEEE Access · doi:10.1109/access.2022.3232440 · Cited by 14

Incentive Mechanism Design for Federated Learning With Dynamic Network Pricing

Ding, N., Gao, L. X., & Huang, J. (2025) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2025.3546977 · Cited by 14

Dynamic behavior assessment protocol for secure Decentralized Federated Learning

Khan, S., Gomes, J., Rehman, M. H. U., & Svetinović, D. (2023) · Internet of Things · doi:10.1016/j.iot.2023.100956 · Cited by 13

When Metaverses Meet Vehicle Road Cooperation: Multiagent DRL-Based Stackelberg Game for Vehicular Twins Migration

Kang, J., Zhang, J., Yang, H., Ye, D., & Hossain, M. S. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3391296 · Cited by 13

Federated learning in smart home: A dynamic contract-based incentive approach with task preferences

Cao, M., Wang, Q., & Wang, Q. (2024) · Computer Networks · doi:10.1016/j.comnet.2024.110510 · Cited by 13

Optimizing Hierarchical Federated Learning: A Reinforcement Learning Approach

Sai, Y., Wu, X., Jiang, J., Huang, Y., Yan, Q., Li, Z., & Huang, H. (2024) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2024.3411674 · Cited by 14

Pedagogical Data Federation toward Education 4.0

Guo, S., & Zeng, D. (2020) · International Conference on Frontiers of Educational Technologies (ICFET) · doi:10.1145/3404709.3404751 · Cited by 13

Federated Learning-Based Risk-Aware Decision to Mitigate Fake Task Impacts on Crowdsensing Platforms

Chen, Z., Şimşek, M., & Kantarcı, B. (2021) · International Conference on Communications · doi:10.1109/icc42927.2021.9500608 · Cited by 13

Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling

Liu, T., Li, P., & Gu, Y. (2021) · International Workshop on Quality of Service · doi:10.1109/iwqos52092.2021.9521331 · Cited by 13

Incentive-Driven Long-term Optimization for Edge Learning by Hierarchical Reinforcement Mechanism

Liu, Y., Wu, L., Zhan, Y., Guo, S., & Hong, Z. (2021) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs51616.2021.00013 · Cited by 13

Fed-DFE: A Decentralized Function Encryption-Based Privacy-Preserving Scheme for Federated Learning

Habib, S., Kiani, G. I., Butt, M. F. U., Abbas, S. M., Aljohani, A. J., & Ng, S. X. (2021) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2022.022290 · Cited by 14

Dynamic Pricing for Client Recruitment in Federated Learning

Wang, X., Zheng, S., & Duan, L. (2023) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2023.3312208 · Cited by 13

Systematic review on privacy-preserving machine learning techniques for healthcare data

Sasirekha, B., & Gunavathi, C. (2025) · Journal of Cyber Security Technology · doi:10.1080/23742917.2025.2511145 · Cited by 16

IoV environment exploring coordination: A federated learning approach

Ding, T. C., Liu, L., Zhu, Y., Cui, L., & Yan, Z. (2022) · Digital Communications and Networks · doi:10.1016/j.dcan.2022.07.006 · Cited by 12

Distributed Mechanism Design in Continuous Space for Federated Learning Over Vehicular Networks

Montazeri, M., Kebriaei, H., Araabi, B. N., Kang, J., & Niyato, D. T. (2022) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2022.3215775 · Cited by 12

Research on Model Optimization Technology of Federated Learning

Dai, H., & Hong, Y. (2023) · IEEE International Conference on Big Data Analytics (ICBDA) · doi:10.1109/icbda57405.2023.10104736 · Cited by 12

FRIMFL: A Fair and Reliable Incentive Mechanism in Federated Learning

Ahmed, A., & Choi, B. J. (2023) · Electronics · doi:10.3390/electronics12153259 · Cited by 12

Utility-Maximizing Bidding Strategy for Data Consumers in Auction-Based Federated Learning

Tang, X., & Yu, H. (2023) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme55011.2023.00064 · Cited by 12

Hwamei: A Learning-Based Synchronization Scheme for Hierarchical Federated Learning

Qi, T., Zhan, Y., Li, P., Guo, J., & Xia, Y. (2023) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs57875.2023.00047 · Cited by 15

A Privacy-Preserving Incentive Scheme for Data Sensing in App-Assisted Mobile Edge Crowdsensing

Xie, L., Su, Z., Chen, N., Wang, Y., Liu, Y., & Li, R. (2024) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2024.3431629 · Cited by 12

Duopoly Business Competition in Cross-Silo Federated Learning

Huang, C., Ke, S., & Liu, X. (2023) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2023.3297880 · Cited by 12

Strategic Coalition for Data Pricing in IoT Data Markets

Pandey, S. R., Pinson, P., & Popovski, P. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3310660 · Cited by 12

Incentive mechanism for collaborative distributed learning in Artificial Intelligence of Things

Wang, G., Yin, J.-L., Hossain, M. S., & Muhammad, G. (2021) · Future Generation Computer Systems · doi:10.1016/j.future.2021.06.015 · Cited by 13

A Novel Joint Dataset and Incentive Management Mechanism for Federated Learning Over MEC

Lee, J., Kim, D., & Niyato, D. T. (2022) · IEEE Access · doi:10.1109/access.2022.3156045 · Cited by 12

Empirical Measurement of Client Contribution for Federated Learning With Data Size Diversification

Shyn, S. K., Kim, D.-H., & Kim, K. (2022) · IEEE Access · doi:10.1109/access.2022.3210950 · Cited by 13

Towards Reliable Federated Learning Using Blockchain-Based Reverse Auctions and Reputation Incentives

Ouyang, K., Yu, J., Cao, X., & Liao, Z. (2023) · Symmetry · doi:10.3390/sym15122179 · Cited by 12

A Novel Incentive Mechanism for Federated Learning Over Wireless Communications

Wang, Y., Zhou, Y. F., & Huang, P.-Q. (2024) · IEEE Transactions on Artificial Intelligence · doi:10.1109/tai.2024.3419757 · Cited by 11

A Two-Stage Secure Incentive Mechanism in App-and UAV-Assisted Crowdsensing

Xie, L., Su, Z., & Wang, Y. (2024) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2024.3439389 · Cited by 11

Strategic Data Revocation in Federated Unlearning

Ding, N., Wei, E., & Berry, R. (2024) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infocom52122.2024.10621201 · Cited by 12

Feeling Without Sharing

Qi, F., Zhang, Z., Yang, X., Zhang, H., & Xu, C. (2022) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3503161.3548278 · Cited by 12

Sustainable Federated Learning with Long-term Online VCG Auction Mechanism

Wu, L., Guo, S., Liu, Y., Hong, Z., Zhan, Y., & Xu, W. (2022) · IEEE International Conference on Distributed Computing Systems (ICDCS) · doi:10.1109/icdcs54860.2022.00091 · Cited by 11

Analysis of Federated Learning as a Distributed Solution for Learning on Edge Devices

Lameh, S. F., Noble, W., Amannejad, Y., & Afshar, A. (2020) · International Conference on Intelligent Data Science Technologies and Applications (IDSTA) · doi:10.1109/idsta50958.2020.9264060 · Cited by 11

Multi-Dimensional Contract-Matching for Federated Learning in UAV-Enabled Internet of Vehicles

Lim, W. Y. B., Huang, J., Xiong, Z., Kang, J., Niyato, D. T., Hua, X., Leung, C., & Miao, C. (2020) · Globecom · doi:10.1109/globecom42002.2020.9322548 · Cited by 11

Optimal Incentive and Load Design for Distributed Coded Machine Learning

Ding, N., Fang, Z., Duan, L., & Huang, J. (2021) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2021.3078494 · Cited by 11

Incentive-Driven Federated Learning and Associated Security Challenges: A Systematic ReviewPreprint

Ali, A., Ilahi, I., Qayyum, A., Mohammed, I., Al‐Fuqaha, A., & Qadir, J. (2021) · doi:10.36227/techrxiv.14945433 · Cited by 13

RRFL: A rational and reliable federated learning incentive framework for mobile crowdsensing

He, Q., Tian, Y., Wang, S., & Xiong, J. (2024) · Journal of King Saud University - Computer and Information Sciences · doi:10.1016/j.jksuci.2024.101977 · Cited by 10

Two-Layer Optimization With Utility Game and Resource Control for Federated Learning in Edge Networks

Tian, F., Zhang, X., Wang, X., & Gong, Y. (2024) · IEEE Transactions on Mobile Computing · doi:10.1109/tmc.2024.3437435 · Cited by 10

Incentive Mechanism Design for Multi-Round Federated Learning With a Single Budget

Ren, Z., Zhang, X., Ng, W. W. Y., & Zhang, J. (2024) · IEEE Transactions on Network Science and Engineering · doi:10.1109/tnse.2024.3488719 · Cited by 11

A Hierarchical Clustering Federated Learning System Based on Industry 4.0

Lu, C.-Y., & Wu, H. (2022) · Journal of Organizational and End User Computing · doi:10.4018/joeuc.313194 · Cited by 10

Strategic Analysis of the Parameter Servers and Participants in Federated Learning: An Evolutionary Game Perspective

Luo, X., Zhang, Z.-L., He, J., & Hu, S. (2022) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2022.3224909 · Cited by 10

Improving Federated Learning through Abnormal Client Detection and Incentive

Guo, H., Mao, Y., He, X., Zhang, B., Pang, T., & Ping, P. (2023) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2023.031466 · Cited by 10

Analysis and evaluation of synchronous and asynchronous FLchain

Wilhelmi, F., Giupponi, L., & Dini, P. (2022) · Computer Networks · doi:10.1016/j.comnet.2022.109390 · Cited by 10

VFL-Chain: Bulletproofing Federated Learning in the V2X environments

Smahi, A., Li, H., Wang, H., Fateh, A. A., & Chan, C. C. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.02.012 · Cited by 9

Dynamic Incentive Design for Federated Learning Based on Consortium Blockchain Using a Stackelberg Game

Han, B., Li, B., Wolter, K., Jurdak, R., Zhang, H. Y., Hu, Y., & Li, Y. (2024) · IEEE Access · doi:10.1109/access.2024.3487585 · Cited by 10

Towards a Decentralized Collaborative Framework for Scalable Edge AI

Abdelmoniem, A. M., Jaber, M., Anwar, A., Zhang, Y., & Gao, M. (2024) · Future Internet · doi:10.3390/fi16110421 · Cited by 9

Hedonic Coalition Formation Game and Contract-Based Federated Learning in AAV-Assisted Internet of Things

Liu, J., Li, X., Xu, Y., Lyu, C., Wang, Y.-C., & Liu, X.-Y. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3543917 · Cited by 11

Eecs-fl: energy-efficient client selection for federated learning in AIoT

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