A genetic programming approach to support the design of service compositions

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

@Article{Aversano:2006:IJCSSE,
  author =       "Lerina Aversano and Massimiliano {Di Penta} and 
                 Kunal Taneja",
  title =        "A genetic programming approach to support the design
                 of service compositions",
  journal =      "International Journal of Computer Systems Science \&
                 Engineering",
  year =         "2006",
  volume =       "21",
  number =       "4",
  pages =        "247--254",
  month =        jul,
  organisation = "Curtin University of Technology, Australia",
  publisher =    "CRL Publishing, admin@crlpublishing.co.uk",
  keywords =     "genetic algorithms, genetic programming, SBSE, service
                 compositions, distributed software, workflow",
  ISSN =         "0267 6192",
  URL =          "http://www.rcost.unisannio.it/mdipenta/papers/csse06.pdf",
  size =         "8 pages",
  oai =          "oai:CiteSeerXPSU:10.1.1.145.843",
  abstract =     "The design of service composition is one of the most
                 challenging research problems in service-oriented
                 software engineering. Building composite services is
                 concerned with identifying a suitable set of services
                 that orchestrated in some way is able to solve a
                 business goal which cannot be resolved using a single
                 service amongst those available. Despite the literature
                 reports several approaches for (semi) automatic service
                 composition, several problems, such as the capability
                 of determining the composition's topology, still remain
                 open. This paper proposes a search-based approach to
                 semi-automatically support the design of service
                 compositions. In particular, the approach uses genetic
                 programming to automatically generate workflows that
                 accomplish a business goal and exhibit a given QoS
                 level, with the aim of supporting the service
                 integrator activities in the finalization of the
                 workflow.",
  notes =        "WSDL, BPEL4WS. GP tree made of sequence, switch flow,
                 loop nodes. Pop=100, Generations=1000, initioal pop<= 5
                 nodes. Fitness based on precision and recall. GP
                 compared with exhuastive search. Cited by
                 \cite{Rodriguez-Mier:2010:EI}, cites \{1068189} GECCO
                 2005. SeCSEP",
}

Genetic Programming entries for Lerina Aversano Massimiliano Di Penta Kunal Taneja

Citations