Edge Computing Task Offloading using Random Forest Regression

Rezaul Fernandez, Imran Alam, Mahmud Ahmed

Open Access Journal of Engineering Applications · doi:10.55555/oajea.2024.4801.038

1. Introduction

Increasing deployment of data centers has exposed clear limitations in existing approaches to edge computing task offloading. A hybrid scheme couples random forest regression with physics-based constraints to improve interpretability. Only 2 of the candidate configurations satisfied every performance requirement. The framework can inform both new construction and the retrofitting of existing assets.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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