Edge Computing Task Offloading using Random Forest Regression
Rezaul Fernandez
Corresponding
Indian Institute of Technology Bombay
Imran Alam
University of Cambridge
Mahmud Ahmed
Indian Institute of Technology Kharagpur
Abstract
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.
Keywords:
edge computing task offloadingrandom forest regressionco2 sequestrationedge computing
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