Load prediction of virtual machine servers using genetic expression programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Hung:2013:iFUZZY,
  author =       "Lung-Hsuan Hung and Chih-Hung Wu",
  booktitle =    "International Conference on Fuzzy Theory and Its
                 Applications (iFUZZY 2013)",
  title =        "Load prediction of virtual machine servers using
                 genetic expression programming",
  year =         "2013",
  month =        dec,
  pages =        "402--406",
  abstract =     "Virtualisation is a key technology for
                 cloud-computing, which creates various types of virtual
                 computing resources on physical machines. A centre of
                 virtual machine (VM) servers manages different load
                 situations of servers and adjusts flexibly the
                 consumptions of physical resources to achieve better
                 cost-performance efficiency. One of the key problems in
                 the management of VM servers (VMSs) is load prediction
                 with which decisions for load-balance as well as other
                 management issues can be engaged. This study employs
                 genetic expression programming (GEP) for deriving
                 regression models of load of VMSs. GEP regression
                 models are white-boxes that have visible structures and
                 can be modified and integrated with other VM management
                 mechanisms. Data representing the types of VM
                 resources, VM loads, etc., are collected for training
                 GEP models. With the GEP models, one can predict the
                 work load of VMSs so that precise decisions of
                 load-balance can be made. The experimental results show
                 that GEP can generate precise models for load
                 prediction of VMSs than other methods.",
  keywords =     "genetic algorithms, genetic programming, genetic
                 expression programming",
  DOI =          "doi:10.1109/iFuzzy.2013.6825473",
  notes =        "Also known as \cite{6825473}",
}

Genetic Programming entries for Lung-Hsuan Hung Chih-Hung Wu

Citations