Component Object Based Single System Image Middleware for Metacomputer Implementation of Genetic Programming on Clusters

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{tanev:2001:ICCS,
  author =       "Ivan Tanev and Takashi Uozumi and Dauren Akhmetov",
  title =        "Component Object Based Single System Image Middleware
                 for Metacomputer Implementation of Genetic Programming
                 on Clusters",
  booktitle =    "Computational Science - ICCS 2001: International
                 Conference",
  year =         "2001",
  editor =       "V. N. Alexandrov and J. J Dongarra and 
                 B. A. Juliano and R. S. Renner and C. J. K. Tan",
  volume =       "2073",
  series =       "LNCS",
  pages =        "284--293",
  address =      "San Francisco, CA, USA",
  publisher_address = "Heidelberg",
  month =        may # " 28-30",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-540-42232-3",
  DOI =          "doi:10.1007/3-540-45545-0_37",
  size =         "10 pages",
  abstract =     "We present a distributed component-object model (DCOM)
                 based single system image middleware (SSIM) for
                 metacomputer implementation of genetic programming
                 (MIGP). MIGP is aimed to significantly improve the
                 computational performance of genetic programming (GP)
                 exploiting the inher-ent parallelism in GP among the
                 evaluation of individuals. It runs on cost-effective
                 clusters of commodity, non-dedicated, heterogeneous
                 workstations. Developed SSIM represents these
                 workstations as a unified virtual resource and
                 addresses the issues of locating and allocating the
                 physical resources, commu-nicating between the entities
                 of MIGP, scheduling and load balance. Adopting DCOM as
                 a communicating paradigm offers the benefits of
                 software platform-and network protocol neutrality of
                 proposed implementation; and the generic support for
                 the issues of locating, allocating and security of the
                 distributed enti-ties of MIGP. Presented results of
                 experimentally obtained speedup character-istics show
                 close to linear speedup of MIGP for solving the time
                 series identifi-cation problem on cluster of 10 W2K
                 workstations.",
}

Genetic Programming entries for Ivan T Tanev Takashi Uozumi Dauren Akhmetov

Citations