Hybrid Recurrent Neural Network and Decision Tree Scheduling for Energy-Efficient Resource Allocation in Cloud Computing
Efficient resource allocation in cloud computing is critical for optimizing execution time, minimizing delays, and improving system reliability. Traditional heuristic-based scheduling approaches struggle to adapt to dynamic workloads and heterogeneous virtual machines (VMs), leading to suboptimal pe...
Saved in:
| Main Authors: | Sefati Seyed Salar, Vulpe Alexandru, Popovici Eduard, Fratu Octavian |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2025-01-01
|
| Series: | EPJ Web of Conferences |
| Online Access: | https://www.epj-conferences.org/articles/epjconf/pdf/2025/11/epjconf_cofmer2025_05007.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SSLA: a semi-supervised framework for real-time injection detection and anomaly monitoring in cloud-based web applications with real-world implementation and evaluation
by: Seyed Salar Sefati, et al.
Published: (2025-07-01) -
Cache Aging with Learning (CAL): A Freshness-Based Data Caching Method for Information-Centric Networking on the Internet of Things (IoT)
by: Nemat Hazrati, et al.
Published: (2025-01-01) -
SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing
by: Ashwin Singh Slathia, et al.
Published: (2025-01-01) -
Resource allocation strategies and task scheduling algorithms for cloud computing: A systematic literature review
by: Kareem Awad Waleed, et al.
Published: (2025-05-01) -
A dual scheduling framework for task and resource allocation in clouds using deep reinforcement learning
by: Jiahui Pan, et al.
Published: (2025-06-01)