Detail publikace

A Proposal for a Federated Learning Protocol for Mobile and Management Systems

MICHÁLEK, J. OUJEZSKÝ, V. HOLÍK, M. ŠKORPIL, V.

Originální název

A Proposal for a Federated Learning Protocol for Mobile and Management Systems

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

In this research paper, we introduce a federated learning communication protocol tailored for emergency management applications. Our primary objective is to tackle the communication challenges that arise in such critical scenarios. In order to overcome the limitations associated with centralized server architectures, we present an innovative communication protocol. This protocol empowers the framework to effectively cooperate with multiple centralized servers, fostering efficient knowledge sharing and model training while ensuring the utmost data privacy and security. By harnessing this protocol, our framework elevates the performance and resilience of vital infrastructure systems operating on the Android platform, thereby facilitating real-time operational scenarios. This research makes a substantial contribution to the field of emergency management applications, as we offer a comprehensive solution that optimizes communication and enables seamless collaboration with numerous centralized servers.

Klíčová slova

Android; communication protocol; federated learning; framework; machine learning; mobile

Autoři

MICHÁLEK, J.; OUJEZSKÝ, V.; HOLÍK, M.; ŠKORPIL, V.

Vydáno

21. 12. 2023

Nakladatel

MDPI

ISSN

2076-3417

Periodikum

Applied Sciences - Basel

Ročník

14

Číslo

1

Stát

Švýcarská konfederace

Strany od

1

Strany do

14

Strany počet

14

URL

https://www.mdpi.com/2076-3417/14/1/101

Plný text v Digitální knihovně

http://hdl.handle.net/11012/245203

BibTex

@article{BUT186768,
  author="Jakub {Michálek} and Václav {Oujezský} and Martin {Holík} and Vladislav {Škorpil}",
  title="A Proposal for a Federated Learning Protocol for Mobile and Management Systems",
  journal="Applied Sciences - Basel",
  year="2023",
  volume="14",
  number="1",
  pages="1--14",
  doi="10.3390/app14010101",
  issn="2076-3417",
  url="https://www.mdpi.com/2076-3417/14/1/101"
}