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Binary PSO for Web Service Location-Allocation

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Artificial Life and Computational Intelligence (ACALCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10142))

Abstract

Web services are independently programmable application components which scatter over the Internet. Network latency is one of the major concerns of web service application. Thus, physical locations of web services and users should be taken into account for web service composition. In this paper, we propose a new solution based on the modified binary PSO-based (MBPSO) approach which employs an adaptive inertia technique to allocating web service locations. Although several heuristic approaches have been proposed for web service location-allocation, to our best knowledge, this is the first time applying PSO to solve the problem. A simulated experiment is done using the WS-DREAM dataset with five different complexities. To compare with genetic algorithm and original binary PSO approaches, the proposed MBPSO approach has advantages in most situations.

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Authors and Affiliations

  1. Victoria University of Wellington, Wellington, New Zealand

    Boxiong Tan, Hai Huang, Hui Ma & Mengjie Zhang

Authors
  1. Boxiong Tan
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  2. Hai Huang
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  3. Hui Ma
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  4. Mengjie Zhang
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Corresponding author

Correspondence to Boxiong Tan .

Editor information

Editors and Affiliations

  1. The University of Adelaide, Adelaide, South Australia, Australia

    Markus Wagner

  2. RMIT University, Melbourne, Victoria, Australia

    Xiaodong Li

  3. Swinburne University, Melbourne, Victoria, Australia

    Tim Hendtlass

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Tan, B., Huang, H., Ma, H., Zhang, M. (2017). Binary PSO for Web Service Location-Allocation. In: Wagner, M., Li, X., Hendtlass, T. (eds) Artificial Life and Computational Intelligence. ACALCI 2017. Lecture Notes in Computer Science(), vol 10142. Springer, Cham. https://doi.org/10.1007/978-3-319-51691-2_31

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  • DOI: https://doi.org/10.1007/978-3-319-51691-2_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51690-5

  • Online ISBN: 978-3-319-51691-2

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