Distributed Service Performance Management Based on Linear Regression and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  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:

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