Adaptive ensemble workload prediction model based on machine learning algorithms

摘要

Workload data associated with past execution of an application by a computing system is obtained. Two or more prediction models are trained using the obtained past workload data. A weight is assigned to each of the two or more trained prediction models. The two or more weighted prediction models are combined to form an ensemble prediction model configured to predict, in real-time, workload associated with future execution of the application by the computing system.