EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments
Abstract The widespread adoption of cloud services has posed several challenges, primarily revolving around energy and resource efficiency. Integrating cloud and fog resources can help address these challenges by improving fog-cloud computing environments. Nevertheless, the search for optimal task a...
Saved in:
| Main Authors: | Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-96974-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fog Offloading and Task Management in IoT-Fog-Cloud Environment: Review of Algorithms, Networks, and SDN Application
by: Mohammad Reza Rezaee, et al.
Published: (2024-01-01) -
Dynamic multi-criteria scheduling algorithm for smart home tasks in fog-cloud IoT systems
by: Ruchika Bhakhar, et al.
Published: (2024-12-01) -
Joint Optimization of Computation Offloading and Task Scheduling Using Multi-Objective Arithmetic Optimization Algorithm in Cloud-Fog Computing
by: Asad Ali, et al.
Published: (2024-01-01) -
Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning
by: Prashanth Choppara, et al.
Published: (2025-01-01) -
A Hybrid Task Scheduling Technique in Fog Computing Using Fuzzy Logic and Deep Reinforcement Learning
by: Prashanth Choppara, et al.
Published: (2024-01-01)