Resource Allocation of Federated Learning Assisted Mobile Augmented Reality System in the Metaverse

Author:

Zhou Xinyu1,Li Yang1,Zhao Jun2

Affiliation:

1. School of Computer Science & Engineering and ERI@N, Nanyang Technological University,Singapore

2. School of Computer Science & Engineering, Nanyang Technological University,Singapore

Publisher

IEEE

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse;Equilibrium. Quarterly Journal of Economics and Economic Policy;2024-06-30

2. Optimized 5G Resource Allocation for Metaverse Applications;2024 International Conference on Electronics, Computing, Communication and Control Technology (ICECCC);2024-05-02

3. Multi-stage Pricing Mechanism in Duopoly Computation Markets;Communications in Computer and Information Science;2024

4. Federated Learning for the Metaverse: A Short Survey;2023 International Conference on Intelligent Metaverse Technologies & Applications (iMETA);2023-09-18

5. Game-o-Meta: Trusted Federated Learning Scheme for P2P Gaming Metaverse beyond 5G Networks;Sensors;2023-04-22

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