Distributed Service Performance Management Based on Linear Regression and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Chen:2005:ICMLC,

• author = "Jing Chen and Zeng-Zhi Li and Zhi-Gang Liao and Yun-Lan Wang",
• title = "Distributed Service Performance Management Based on Linear Regression and Genetic Programming",
• booktitle = "Proceedings of 2005 International Conference on Machine Learning and Cybernetics",
• year = "2005",
• volume = "1",
• pages = "560--563",
• month = "18-21 " # aug,
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ICMLC.2005.1527007",
• abstract = "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.",
• notes = "Telecommunication Engineering Institute, Air Force Engineering University, Xi'an 710077, China; Institute of Computer System Architecture & Network, Xi'an Jiaotong University, Xi'an 710049, China E-MAIL: jingchen@263.net",

}

Genetic Programming entries for Jing Chen Zeng-zhi Li Zhi-Gang Liao Yun-Lan Wang

Citations