Journal article2023IEEE Communications Surveys & Tutorials

Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges

SurveysData modelsSecurityFederated learningTutorialsServersOptimizationDecentralized federated learningcommunication mechanismssecurity and privacykey performance indicatorsframeworksapplication scenarios

Quick facts

Year
2023
Venue
IEEE Communications Surveys & Tutorials
Identifier
martinezbeltran2023decentralized

Suggested citation

Enrique Tomás Martínez Beltrán, Mario Quiles Pérez, Pedro Miguel Sánchez Sánchez, Sergio López Bernal, Gérôme Bovet, Manuel Gil Pérez, Gregorio Martínez Pérez, Alberto Huertas Celdrán (2023). Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges. IEEE Communications Surveys & Tutorials.

Abstract

Authors

Enrique Tomás Martínez BeltránMario Quiles PérezPedro Miguel Sánchez SánchezSergio López BernalGérôme BovetManuel Gil PérezGregorio Martínez PérezAlberto Huertas Celdrán

Keywords

SurveysData modelsSecurityFederated learningTutorialsServersOptimizationDecentralized federated learningcommunication mechanismssecurity and privacykey performance indicatorsframeworksapplication scenarios

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