Strategic Analysis of the Parameter Servers and Participants in Federated Learning
An Evolutionary Game Perspective
Bibliographic Data
| ID | 22108945 |
|---|---|
| Authors | Xinggang Luo (0000-0002-7689-8449, Hangzhou Dianzi University), Zhongliang Zhang (0009-0001-1364-8012, Hangzhou Dianzi University), Zhong-Liang Zhang (0000-0001-6555-7908, Hangzhou Dianzi University), Jiahuan He (0000-0001-7331-9328, Northeastern University), Shengnan Hu (0000-0002-7771-7339, Hangzhou Dianzi University) |
| Year | 2024 |
| Volume | 11 |
| Issue | 1 |
| Pages | 132-143 |
| Publication date | 2024-02-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2022.3224909 |
| OpenAlex | W4313187560 |
| Language | EN |
| Citations received | 2 |
| References cited | 37 |
Federated learning (FL) is a new decentralized deep learning paradigm developed for collaborative model training and solving the problem of data privacy and has received extensive attention from both the academic and business worlds. However, FL still faces challenges in encouraging participants to contribute private data and computational resources. Although many studies have applied game theory models to improve the incentive mechanism design of FL, they assume that the players are absolutely rational and that the game models are static. In this study, a mathematical model based on evolutionary game theory (EGT) is established to analyze the interaction between parameter servers and participants, considering that the participants are not completely rational in the long-term dynamic decision-making process. The evolutionarily stable status of the FL system and the strategies of the parameter servers and participants were analyzed under eight different scenarios. Based on the model analysis and results of the numerical experiments, managerial insights for maintaining a sustainable FL system are summarized
Economics · Evolutionarily stable strategy · Evolutionary game theory · Game theory · Incentive · Knowledge management · Management science · Microeconomics · Server · Computer Science · Engineering · Mobile Crowdsensing and Crowdsourcing · Privacy-Preserving Technologies in Data · Privacy, Security, and Data Protection · Artificial Intelligence
| Unique citing works | 2 |
|---|---|
| Citations per year | 1 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 2 |