2016 IEEE 15th International Symposium on Network Computing and Applications (NCA)
Download PDF

Abstract

The objective of this paper is to analyze the use of nonlinear models to predict the CPU frequency that reaches the lowest power consumption of a smartphone based on Android OS context variables. Artificial neural networks (ANNs) and k-nearest neighbors (k-NN) techniques are investigated, and their results are compared to those obtained by the linear method (LM). Experimental results indicate the k-NN technique is the best option in terms of model accuracy and performance when compared to the other prediction models.
Like what you’re reading?
Already a member?
Get this article FREE with a new membership!

Related Articles