Incentive mechanisms for federated learning: From economic and game theoretic perspective
Federated learning (FL) becomes popular and has shown great potentials in training large-
scale machine learning (ML) models without exposing the owners' raw data. In FL, the data …
scale machine learning (ML) models without exposing the owners' raw data. In FL, the data …
Middleware for the Internet of Things: A survey on requirements, enabling technologies, and solutions
As the core layer of the Internet of Things (IoT), middleware bridges the gap between
applications and devices to resolve many common IoT issues and enhancing application …
applications and devices to resolve many common IoT issues and enhancing application …
A systematic review of federated learning incentive mechanisms and associated security challenges
In response to various privacy risks, researchers and practitioners have been exploring
different paradigms that can leverage the increased computational capabilities of consumer …
different paradigms that can leverage the increased computational capabilities of consumer …
Multi-criteria handover mobility management in 5G cellular network
To fulfill the future demand and expansion of the coverage of the network, ultra-dense
deployment of small cell (SC) is an optimal solution for future 5G networks, which will ensure …
deployment of small cell (SC) is an optimal solution for future 5G networks, which will ensure …
Optimal Transport based one-shot federated learning for artificial intelligence of things
Federated learning (FL) is an emerging distributed machine learning (ML) paradigm in the
Artificial Intelligence of Things (AIoT). FL enables AIoT devices to collaboratively train an ML …
Artificial Intelligence of Things (AIoT). FL enables AIoT devices to collaboratively train an ML …
[HTML][HTML] Review on application progress of federated learning model and security hazard protection
Federated learning is a new type of distributed learning framework that allows multiple
participants to share training results without revealing their data privacy. As data privacy …
participants to share training results without revealing their data privacy. As data privacy …
Utility-maximizing bidding strategy for data consumers in auction-based federated learning
Auction-based Federated Learning (AFL) has attracted extensive research interest due to its
ability to motivate data owners to join FL through economic means. Existing works assume …
ability to motivate data owners to join FL through economic means. Existing works assume …
A review on client selection models in federated learning
Federated learning (FL) is a decentralized machine learning (ML) technique that enables
multiple clients to collaboratively train a common ML model without them having to share …
multiple clients to collaboratively train a common ML model without them having to share …
Energy cooperation among sustainable base stations in multi-operator cellular networks
A Tahsin, P Roy, MA Razzaque… - IEEE …, 2023 - ieeexplore.ieee.org
Energy Harvesting technology contributes significantly to green cellular networking by
ensuring self-sustainability and extinguishing environmental hazards. Due to the imbalance …
ensuring self-sustainability and extinguishing environmental hazards. Due to the imbalance …
Advances and open challenges in federated learning with foundation models
Abstract The integration of Foundation Models (FMs) with Federated Learning (FL) presents
a transformative paradigm in Artificial Intelligence (AI), offering enhanced capabilities while …
a transformative paradigm in Artificial Intelligence (AI), offering enhanced capabilities while …