Deep Reinforcement Learning for Workload Prediction in Federated Cloud Environments

Deep Reinforcement Learning for Workload Prediction in Federated Cloud Environments

The Federated Cloud Computing (FCC) paradigm provides scalability advantages to Cloud Service Providers (CSP) in preserving their Service Level Agreement (SLA) as opposed to single Data Centers (DC). However, existing research has primarily focused on Virtual Machine (VM) placement, with less emphas...

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Bibliographic Details
Main Authors: Zaakki Ahamed, Maher Khemakhem, Fathy Eassa, Fawaz Alsolami, Abdullah Basuhail, Kamal Jambi
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Sensors
Subjects:
Deep Reinforcement Learning
Deep Q learning
workload prediction
Federated Cloud Computing
energy efficiency
Virtual Machine placement
Online Access:https://www.mdpi.com/1424-8220/23/15/6911

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https://www.mdpi.com/1424-8220/23/15/6911

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