Energy-efficient distributed federated learning offloading and scheduling healthcare system in blockchain based networks?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10252839" target="_blank" >RIV/61989100:27240/23:10252839 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2542660523001385" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2542660523001385</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.iot.2023.100815" target="_blank" >10.1016/j.iot.2023.100815</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Energy-efficient distributed federated learning offloading and scheduling healthcare system in blockchain based networks?

Popis výsledku v původním jazyce

Many disease detection and prevention applications in digital healthcare systems are widely used but often focus only on prediction and classification, ignoring processing performance and data privacy issues. The study investigates the Energy-Efficient Distributed Federated Learning Offloading and Scheduling Healthcare Systems in Blockchain-Based Networks problem for healthcare applications. In order to solve the problem, the study presents the Energy-Efficient Distributed Federated Learning Offloading and Scheduling (EDFOS) system in blockchain based networks. EDFOS consisted of different schemes such as energy efficient offloading and scheduling and meet the quality of services (QoS) of applications during performing in the system. Simulation results show that EDFOS reduces power consumption by 39%, training and testing time by 29%, and resource leakage and deadlines by 36% compared to existing healthcare systems. The EDFOS platform is an effective solution for addressing the issues of power consumption and data privacy in healthcare applications.

Název v anglickém jazyce

Energy-efficient distributed federated learning offloading and scheduling healthcare system in blockchain based networks?

Popis výsledku anglicky

Many disease detection and prevention applications in digital healthcare systems are widely used but often focus only on prediction and classification, ignoring processing performance and data privacy issues. The study investigates the Energy-Efficient Distributed Federated Learning Offloading and Scheduling Healthcare Systems in Blockchain-Based Networks problem for healthcare applications. In order to solve the problem, the study presents the Energy-Efficient Distributed Federated Learning Offloading and Scheduling (EDFOS) system in blockchain based networks. EDFOS consisted of different schemes such as energy efficient offloading and scheduling and meet the quality of services (QoS) of applications during performing in the system. Simulation results show that EDFOS reduces power consumption by 39%, training and testing time by 29%, and resource leakage and deadlines by 36% compared to existing healthcare systems. The EDFOS platform is an effective solution for addressing the issues of power consumption and data privacy in healthcare applications.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

20200 - Electrical engineering, Electronic engineering, Information engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Internet of Things

ISSN

2543-1536

e-ISSN

2542-6605

Svazek periodika

22

Číslo periodika v rámci svazku

2023

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

1-13

Kód UT WoS článku

001056598900001

EID výsledku v databázi Scopus

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