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Found 8 papers, 0 papers with code
Tiny Multi-Agent DRL for Twins Migration in UAV Metaverses: A Multi-Leader Multi-Follower Stackelberg Game Approach
To address the challenges, we propose a tiny machine learning-based Stackelberg game framework based on pruning techniques for efficient UT migration in UAV metaverses.
Service Reservation and Pricing for Green Metaverses: A Stackelberg Game Approach
A single-leader multi-follower Stackelberg game is formulated between the MSP and users while each user optimizes an offloading probability to minimize the weighted sum of time, energy consumption and monetary cost.
Federated Learning-Empowered AI-Generated Content in Wireless Networks
Artificial intelligence generated content (AIGC) has emerged as a promising technology to improve the efficiency, quality, diversity and flexibility of the content creation process by adopting a variety of generative AI models.
Adversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses
In this article, we propose a hierarchical SemCom-enabled vehicular metaverses framework consisting of the global metaverse, local metaverses, SemCom module, and resource pool.
AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices
We propose a cost-adjustable FL framework, named AnycostFL, that enables diverse edge devices to efficiently perform local updates under a wide range of efficiency constraints.
FedGreen: Federated Learning with Fine-Grained Gradient Compression for Green Mobile Edge Computing
Federated learning (FL) enables devices in mobile edge computing (MEC) to collaboratively train a shared model without uploading the local data.
FedParking: A Federated Learning based Parking Space Estimation with Parked Vehicle assisted Edge Computing
In PVEC, different PLOs recruit PVs as edge computing nodes for offloading services through an incentive mechanism, which is designed according to the computation demand and parking capacity constraints derived from FedParking.
Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks
Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i. e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources.
