Towards Efficient Federated Learning of Networked Mixture-of-Experts for Mobile Edge Computing
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Gao, Song, Zhang, Songyang, Jing, Shusen, Zhang, Shuai, Zhou, Xiangwei, Wang, Yue, Cai, Zhipeng |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Toward Scalable Generative AI via Mixture of Experts in Mobile Edge Networks
par: Wang, Jiacheng, et autres
Publié: (2024)
par: Wang, Jiacheng, et autres
Publié: (2024)
Energy-Efficient Online Scheduling for Wireless Powered Mobile Edge Computing Networks
par: He, Xingqiu, et autres
Publié: (2026)
par: He, Xingqiu, et autres
Publié: (2026)
Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse
par: Liu, Guangyuan, et autres
Publié: (2024)
par: Liu, Guangyuan, et autres
Publié: (2024)
EMS-FL: Federated Tuning of Mixture-of-Experts in Satellite-Terrestrial Networks via Expert-Driven Model Splitting
par: Xu, Angzi, et autres
Publié: (2026)
par: Xu, Angzi, et autres
Publié: (2026)
EdgeTimer: Adaptive Multi-Timescale Scheduling in Mobile Edge Computing with Deep Reinforcement Learning
par: Hao, Yijun, et autres
Publié: (2024)
par: Hao, Yijun, et autres
Publié: (2024)
Toward Resource-Efficient Collaboration of Large AI Models in Mobile Edge Networks
par: Li, Peichun, et autres
Publié: (2026)
par: Li, Peichun, et autres
Publié: (2026)
LeFi: Learn to Incentivize Federated Learning in Automotive Edge Computing
par: Zhao, Ming, et autres
Publié: (2023)
par: Zhao, Ming, et autres
Publié: (2023)
Toward Democratized Generative AI in Next-Generation Mobile Edge Networks
par: Zhang, Ruichen, et autres
Publié: (2024)
par: Zhang, Ruichen, et autres
Publié: (2024)
VEC-Sim: A Simulation Platform for Evaluating Service Caching and Computation Offloading Policies in Vehicular Edge Networks
par: Wu, Fan, et autres
Publié: (2024)
par: Wu, Fan, et autres
Publié: (2024)
Energy-Efficient Federated Learning and Migration in Digital Twin Edge Networks
par: Zhou, Yuzhi, et autres
Publié: (2025)
par: Zhou, Yuzhi, et autres
Publié: (2025)
SCALE: Sensitivity-Aware Federated Unlearning with Information Freshness Optimization for Mobile Edge Computing
par: Ding, Zihao, et autres
Publié: (2026)
par: Ding, Zihao, et autres
Publié: (2026)
Accelerating Handover in Mobile Satellite Network
par: Wu, Jiasheng, et autres
Publié: (2024)
par: Wu, Jiasheng, et autres
Publié: (2024)
Federated Learning for Iot/Edge/Fog Computing Systems
par: Hasan, Balqees Talal, et autres
Publié: (2024)
par: Hasan, Balqees Talal, et autres
Publié: (2024)
Optimized Federated Multitask Learning in Mobile Edge Networks: A Hybrid Client Selection and Model Aggregation Approach
par: Hamood, Moqbel, et autres
Publié: (2024)
par: Hamood, Moqbel, et autres
Publié: (2024)
Energy Efficient and Balanced Task Assignment Strategy for Multi-UAV Patrol Inspection System in Mobile Edge Computing Network
par: Jia, Kuan, et autres
Publié: (2024)
par: Jia, Kuan, et autres
Publié: (2024)
EcoEdgeTwin: Enhanced 6G Network via Mobile Edge Computing and Digital Twin Integration
par: Karobi, Synthia Hossain, et autres
Publié: (2024)
par: Karobi, Synthia Hossain, et autres
Publié: (2024)
Play to Earn in the Metaverse with Mobile Edge Computing over Wireless Networks: A Deep Reinforcement Learning Approach
par: Chua, Terence Jie, et autres
Publié: (2023)
par: Chua, Terence Jie, et autres
Publié: (2023)
Multi-Tier UAV Edge Computing for Low Altitude Networks Towards Long-Term Energy Stability
par: Ye, Yufei, et autres
Publié: (2025)
par: Ye, Yufei, et autres
Publié: (2025)
Multi-Tier UAV Edge Computing Towards Long-Term Energy Stability for Low Altitude Networks
par: Ye, Yufei, et autres
Publié: (2026)
par: Ye, Yufei, et autres
Publié: (2026)
Optimizing Generative AI Networking: A Dual Perspective with Multi-Agent Systems and Mixture of Experts
par: Zhang, Ruichen, et autres
Publié: (2024)
par: Zhang, Ruichen, et autres
Publié: (2024)
On the Optimization of Model Aggregation for Federated Learning at the Network Edge
par: Li, Mengyao, et autres
Publié: (2025)
par: Li, Mengyao, et autres
Publié: (2025)
Admission Control with Reconfigurable Intelligent Surfaces for 6G Mobile Edge Computing
par: Zhang, Ye, et autres
Publié: (2025)
par: Zhang, Ye, et autres
Publié: (2025)
Compact LLM Deployment and World Model Assisted Offloading in Mobile Edge Computing
par: Zhang, Ruichen, et autres
Publié: (2026)
par: Zhang, Ruichen, et autres
Publié: (2026)
Digital Twin-Enabled Mobility-Aware Cooperative Caching in Vehicular Edge Computing
par: Zeng, Jiahao, et autres
Publié: (2026)
par: Zeng, Jiahao, et autres
Publié: (2026)
Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
par: Xu, Minrui, et autres
Publié: (2025)
par: Xu, Minrui, et autres
Publié: (2025)
PHandover: Parallel Handover in Mobile Satellite Network
par: Wu, Jiasheng, et autres
Publié: (2025)
par: Wu, Jiasheng, et autres
Publié: (2025)
Joint Optimization of DNN Model Caching and Request Routing in Mobile Edge Computing
par: Qiu, Shuting, et autres
Publié: (2025)
par: Qiu, Shuting, et autres
Publié: (2025)
Bayesian Optimization for Online Management in Dynamic Mobile Edge Computing
par: Yan, Jia, et autres
Publié: (2022)
par: Yan, Jia, et autres
Publié: (2022)
Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories
par: Yang, Ning, et autres
Publié: (2024)
par: Yang, Ning, et autres
Publié: (2024)
Empowering the Edge Intelligence by Air-Ground Integrated Federated Learning
par: Qu, Yuben, et autres
Publié: (2020)
par: Qu, Yuben, et autres
Publié: (2020)
RRTO: A High-Performance Transparent Offloading System for Model Inference in Mobile Edge Computing
par: Sun, Zekai, et autres
Publié: (2025)
par: Sun, Zekai, et autres
Publié: (2025)
Advancements in Mobile Edge Computing and Open RAN: Leveraging Artificial Intelligence and Machine Learning for Wireless Systems
par: Barker, Ryan, et autres
Publié: (2025)
par: Barker, Ryan, et autres
Publié: (2025)
SpaceMoE: Towards Orbital General Intelligence with Distributed Mixture-of-Experts Inference
par: Chen, Qian, et autres
Publié: (2026)
par: Chen, Qian, et autres
Publié: (2026)
Federated Edge Learning for Predictive Maintenance in 6G Small Cell Networks
par: Sezgin, Yusuf Emir, et autres
Publié: (2025)
par: Sezgin, Yusuf Emir, et autres
Publié: (2025)
Moving Edge for On-Demand Edge Computing: An Uncertainty-aware Approach
par: Zhou, Fangtong, et autres
Publié: (2025)
par: Zhou, Fangtong, et autres
Publié: (2025)
FluxShard: Motion-Aware Feature Cache Reuse for Collaborative Video Analytics in Mobile Edge Computing
par: Guan, Xiuxian, et autres
Publié: (2026)
par: Guan, Xiuxian, et autres
Publié: (2026)
Cross: A Delay Based Congestion Control Method for RTP Media
par: Zhang, Songyang, et autres
Publié: (2024)
par: Zhang, Songyang, et autres
Publié: (2024)
Mixture of Experts for Decentralized Generative AI and Reinforcement Learning in Wireless Networks: A Comprehensive Survey
par: Xu, Yunting, et autres
Publié: (2025)
par: Xu, Yunting, et autres
Publié: (2025)
FedPEAT: Convergence of Federated Learning, Parameter-Efficient Fine Tuning, and Emulator Assisted Tuning for Artificial Intelligence Foundation Models with Mobile Edge Computing
par: Chua, Terence Jie, et autres
Publié: (2023)
par: Chua, Terence Jie, et autres
Publié: (2023)
Federated Parameter-Efficient Adaptation for Interference Mitigation at the Wireless Edge
par: Jones, Evar, et autres
Publié: (2026)
par: Jones, Evar, et autres
Publié: (2026)
Documents similaires
-
Toward Scalable Generative AI via Mixture of Experts in Mobile Edge Networks
par: Wang, Jiacheng, et autres
Publié: (2024) -
Energy-Efficient Online Scheduling for Wireless Powered Mobile Edge Computing Networks
par: He, Xingqiu, et autres
Publié: (2026) -
Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse
par: Liu, Guangyuan, et autres
Publié: (2024) -
EMS-FL: Federated Tuning of Mixture-of-Experts in Satellite-Terrestrial Networks via Expert-Driven Model Splitting
par: Xu, Angzi, et autres
Publié: (2026) -
EdgeTimer: Adaptive Multi-Timescale Scheduling in Mobile Edge Computing with Deep Reinforcement Learning
par: Hao, Yijun, et autres
Publié: (2024)