IDEAS home Printed from https://ideas.repec.org/a/igg/jeis00/v12y2016i3p60-77.html
   My bibliography  Save this article

QoS-based Web Service Composition Applying an Improved Genetic Algorithm (IGA) Method

Author

Listed:
  • Pooya Shahrokh

    (Department of Computer Engineering, Zanjan Branch, Islamic Azad University, Zanjan, Iran)

  • Faramarz Safi-Esfahani

    (Faculty of Computer Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran)

Abstract

In recent years, it has been made possible to compose exiting services when a user's request cannot be satisfied by a single web service. Web service composition is faced with several challenges among which is the rapid growth in the number of available web services leading to increased number of web services offering the same functionalities. The difference between similar services is Quality of Service (QoS) consisting of various non-functional factors such as execution time, availability, security, etc. As a result, multiple choices are possible in making a composition plan. Among numerous plans, selecting a composition plan that fulfills customer's requirements has become an important and time-consuming problem. In this paper, the researchers propose a semi-heuristic genetic algorithm that is a combination of both a heuristic method and the genetic algorithm. This heuristic method changes chromosomes based on unsatisfied constraints. Research findings show that the proposed method can be applied to find a composition plan that satisfies user's requirements more efficiently than other methods.

Suggested Citation

  • Pooya Shahrokh & Faramarz Safi-Esfahani, 2016. "QoS-based Web Service Composition Applying an Improved Genetic Algorithm (IGA) Method," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 12(3), pages 60-77, July.
    • Handle: RePEc:igg:jeis00:v:12:y:2016:i:3:p:60-77
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEIS.2016070104
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jeis00:v:12:y:2016:i:3:p:60-77. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.