Novel Unsupervised Cluster Reinforcement Q-Learning in Minimizing Energy Consumption of Federated Edge Cloud

Novel Unsupervised Cluster Reinforcement Q-Learning in Minimizing Energy Consumption of Federated Edge Cloud

As global demand for cloud computing rises, green computing has become essential. Federated Edge Cloud (FEC) offers improved energy efficiency compared to traditional infrastructures, yet managing distributed energy consumption remains a challenge. This research introduces an Unsupervised Cluster Re...

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Bibliographic Details
Main Authors: Guruh Fajar Shidik, Oki Setiono, Edi Jaya Kusuma, L. Budi Handoko, Pulung Nurtantio Andono, Mohd Faizal Abdollah
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Clustering method
energy efficiency
federated edge cloud
Q-learning
quality of service
Online Access:https://ieeexplore.ieee.org/document/11008640/
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https://ieeexplore.ieee.org/document/11008640/

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