An Adaptive Genetic Programming Approach to QoS-aware Web Services Composition

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

@InProceedings{Yu:2013:CECa,
  article_id =   "1168",
  author =       "Yang Yu and Hui Ma and Mengjie Zhang",
  title =        "An Adaptive Genetic Programming Approach to
                 {QoS}-aware Web Services Composition",
  booktitle =    "2013 IEEE Conference on Evolutionary Computation",
  volume =       "1",
  year =         "2013",
  month =        jun # " 20-23",
  editor =       "Luis Gerardo {de la Fraga}",
  pages =        "1740--1747",
  address =      "Cancun, Mexico",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4799-0453-2",
  DOI =          "doi:10.1109/CEC.2013.6557771",
  abstract =     "Web services are software entities that can be
                 deployed, discovered and invoked in the distributed
                 environment of the Internet through a set of standards
                 such as Simple Object Access Protocol (SOAP), Web
                 Services Description Language (WSDL) and Universal
                 Description, Discovery and Integration (UDDI). However,
                 atomic web service can only provide simple
                 functionality. A range of web services are required to
                 be incorporated into one composite service in order to
                 offer value-added and complicated functionality when no
                 existing web service can be found to satisfy users'
                 request. In service-oriented architecture (SOA), web
                 services composition has become an efficient solution
                 to support business-to-business and enterprise
                 application integration (EAI). In addition to
                 functional properties (i.e., inputs and outputs), web
                 services have non-functional properties called quality
                 of service (QoS) that encompasses a number of
                 parameters such as execution cost, response time and
                 availability. Nowadays with the rapid increase in the
                 number of available web services, a great number of
                 services provide overlapping or identical functionality
                 but vary in QoS attribute values. Due to the huge
                 search space of the composition problem, a genetic
                 programming (GP) approach is proposed in this paper,
                 which aims to produce the desired outputs based on
                 available inputs, as well as ensure that the composite
                 service has the optimal QoS value. Furthermore, an
                 adaptive method is applied to the standard form of GP
                 in order to avoid low rate of convergence and premature
                 convergence. A series of experiments have been
                 conducted to evaluate the proposed approach, and the
                 results show that the adaptive genetic programming
                 approach (AGP) has a good performance in finding a
                 valid solution within low search time and is superior
                 to the traditional approaches",
  notes =        "Quality of service. CEC 2013 - A joint meeting of the
                 IEEE, the EPS and the IET.",
}

Genetic Programming entries for Yang Yu Hui Ma Mengjie Zhang

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