Execution time prediction for grid infrastructures based on runtime provenance data
Muhammad Junaid Malik, Thomas Fahringer, Radu Prodan · 2013
An accurate performance prediction service can be very useful for resource management and the scheduler service and help them make better resource utilization decisions by providing better execution time estimates. In this paper we present a novel approach of predicting the execution time of computational tasks for Grid infrastructures using machine learning models based on multilayer perceptron combined with a principal feature selection algorithm for selecting the most important runtime features.