Distributed Service Performance Management Based on Linear Regression and Genetic Programming

An architecture for online discovery quantitative models system of service performance management was proposed. The system was capable of constructing the quantitative models without prior knowledge of the managed elements. The model can be updated continuously in response to the changes made in provider configurations and the evolution of business demands. Due to the existence of strong correlation between the distributed service metrics and response times, a linear and a hyper-linear quantitative models are constructed, which respectively use the stepwise multiple linear regression and genetic programming algorithms. The simulation results show that the effectiveness of quantitative model constructing system and model constructing algorithms.