Cloud-edge hybrid deep learning framework for scalable IoT resource optimization

Cloud-edge hybrid deep learning framework for scalable IoT resource optimization

Abstract In the dynamic environment of the Internet of Things (IoT), edge and cloud computing play critical roles in analysing and storing data from numerous connected devices to produce valuable insights. Efficient resource allocation and workload distribution are vital to ensuring continuous and r...

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Bibliographic Details
Main Authors: Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani
Format: Article
Language:English
Published: SpringerOpen 2025-02-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Cloud load balancing
IoT edge networks
Deep Q-Networks
Proximal policy optimization
GNN
Reinforcement learning
Online Access:https://doi.org/10.1186/s13677-025-00729-w
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https://doi.org/10.1186/s13677-025-00729-w

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