EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments

Asfandyar Khan, Faizan Ullah, Dilawar Shah, Muhammad Haris Khan, Shujaat Ali, Muhammad Tahir

Open source

DOI
10.1038/s41598-025-96974-9
Published
2025-04-10
Container
Scientific Reports
Publisher
Springer Science and Business Media LLC
Open access
unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1038/s41598-025-96974-9,
  title = {EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments},
  author = {Asfandyar Khan and Faizan Ullah and Dilawar Shah and Muhammad Haris Khan and Shujaat Ali and Muhammad Tahir},
  year = {2025},
  journal = {Scientific Reports},
  doi = {10.1038/s41598-025-96974-9},
  url = {https://doi.org/10.1038/s41598-025-96974-9}
}

RIS

TY  - JOUR
TI  - EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments
AU  - Asfandyar Khan
AU  - Faizan Ullah
AU  - Dilawar Shah
AU  - Muhammad Haris Khan
AU  - Shujaat Ali
AU  - Muhammad Tahir
PY  - 2025
JO  - Scientific Reports
DO  - 10.1038/s41598-025-96974-9
UR  - https://doi.org/10.1038/s41598-025-96974-9
ER  - 

APA

Khan, A., Ullah, F., Shah, D., Khan, M. H., Ali, S., & Tahir, M. (2025). EcoTaskSched: a hybrid machine learning approach for energy-efficient task scheduling in IoT-based fog-cloud environments. Scientific Reports. https://doi.org/10.1038/s41598-025-96974-9

Source records