Cloud Resource Scheduling using Model Predictive Control
Feng Tanaka
Corresponding
Politecnico di Milano
Md Malik
Bangladesh University of Engineering and Technology
Abstract
Conventional approaches to semiconductor fabrication often treat cloud resource scheduling as a secondary consideration, at considerable cost. Laboratory specimens are subjected to controlled loading, and the resulting data processed using model predictive control. Over a period of 5 months, the monitored system exhibited stable and predictable behaviour. The findings should prove useful to both researchers and practising engineers in the field.
Keywords:
cloud resource schedulingmodel predictive controlheat transferheavy metal removaledge computingwavelet transform
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