A Hybrid Approach Using Genetic Programming and Greedy Search for QoS-Aware Web Service Composition

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

@Article{journals/tlsdkcs/MaWZ15,
  author =       "Hui Ma and Anqi Wang and Mengjie Zhang",
  title =        "A Hybrid Approach Using Genetic Programming and Greedy
                 Search for {QoS}-Aware Web Service Composition",
  journal =      "Transactions on Large-Scale Data and
                 Knowledge-Centered Systems",
  bibdate =      "2015-02-24",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/tlsdkcs/tlsdkcs18.html#MaWZ15",
  year =         "2015",
  volume =       "8980",
  editor =       "Abdelkader Hameurlain and Josef Kueng and 
                 Roland Wagner and Hendrik Decker and Lenka Lhotska and 
                 Sebastian Link",
  isbn13 =       "978-3-662-46484-7",
  pages =        "180--205",
  series =       "Lecture Notes in Computer Science",
  note =         "{XVIII} - Special Issue on Database and Expert-Systems
                 Applications",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://dx.doi.org/10.1007/978-3-662-46485-4",
  DOI =          "doi:10.1007/978-3-662-46485-4_7",
  abstract =     "Service compositions build new web services by
                 orchestrating sets of existing web services provided in
                 service repositories. Due to the increasing number of
                 available web services, the search space for finding
                 best service compositions is growing exponentially.
                 Further, there are many available web services that
                 provide identical functionality but differ in their
                 Quality of Service (QoS). Decisions need to be made to
                 determine which services are selected to participate in
                 service compositions with optimized QoS properties.

                 In this paper, a hybrid approach to service composition
                 is proposed that combines the use of genetic
                 programming and random greedy search. The greedy
                 algorithm is used to generate valid and locally
                 optimized individuals to populate the initial
                 generation for genetic programming (GP), and to perform
                 mutation operations during genetic programming.

                 A full experimental evaluation has been carried out
                 using public benchmark test cases with repositories of
                 up to 15,000 web services and 31,000 properties. The
                 results show good performance in searching for best
                 service compositions, where the number of atomic web
                 services used and the tree depth are used as objectives
                 for minimization.

                 Further, we extend our approach to the more general
                 problem of finding service composition solutions that
                 have near-optimal QoS. Our experimental evaluation
                 demonstrates that our GP-based greedy algorithm
                 enhanced approach can be applied with good performance
                 to the QoS-aware service composition problem.",
  notes =        "Preface

                 The 24th International Conference on Database and
                 Expert Systems Applications (DEXA 2013), with
                 proceedings published as volumes 8055 and 8056 in
                 Springer's Lecture Notes in Computer Science, featured
                 some outstanding keynote presentations and regular
                 articles. As with previous editions of the DEXA
                 conference, the Program Co-chairs of DEXA 2013 invited
                 some of the authors to submit extended papers to a
                 special issue of the Springer journal Transactions on
                 Large-Scale Data- and Knowledge- Centred Systems
                 (TLDKS). Following these invitations, both keynote
                 papers and eight regular articles were submitted. Apart
                 from the keynotes, each submission was carefully
                 assessed by at least two (often more) recognized
                 experts in the respective field. In total, 35 reviews
                 were received, most of them of excellent quality. After
                 two rounds of revisions, five of the eight regular
                 papers were accepted for inclusion in this special
                 issue, in addition to the two keynote papers...

                 Cites \cite{Aversano:2006:IJCSSE} Aversano:2005:WSEC",
}

Genetic Programming entries for Hui Ma Anqi Wang Mengjie Zhang

Citations