Performance analysis with self-organizing map and recurrent neural network

Abstract

As software aging has been discovered in many fields, some time-series methods are utilized to find a better time to make a software system become more resilient from the degradation states. However, those existing methods cannot well solve the sequence relationship of the resource consumption series in the aging problems since data series contains linear and nonlinear characteristics. In this paper, we propose a method, recurrent neural network with self-organizing map, to enhance the prediction accuracy for resource consumption series of software aging problems. In order to smooth the resource consumption series, a pre-processing process and a self-organizing map are used. To make the prediction more accurate, a recurrent neural network is used. In the experiment, the proposed method is applied to two types of resource consumption series, and the result shows that our proposed method owns better performances in two aspects.