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Trust Based Service Selection in Service Oriented Environment

Author

Listed:
  • Jun Li

    (College of Computer Science, Zhejiang University, China)

  • Xiaolin Zheng

    (College of Computer Science, Zhejiang University, China)

  • Deren Chen

    (College of Computer Science, Zhejiang University, China)

  • William Wei Song

    (Dalarna University, Sweden)

Abstract

In a service-oriented environment, it is inevitable and indeed quite common to deal with web services, whose reliability is unknown to the users. The reputation system is a popular technique currently used for providing a global quality score of a service provider to requesters. However, such global information is far from sufficient for service requesters to choose the most qualified services. In order to tackle this problem, the authors present a trust based architecture containing a computational trust model for quantifying and comparing the trustworthiness of services. In this trust model, they firstly construct a network based on the direct trust relations between participants and rating similarity in service oriented environments, then propose an algorithm for propagating trust in the social network based environment which can produce personalized trust information for a specific service requester, and finally implement the trust model and simulate various malicious behaviors in not only dense but also sparse networks which can verify the attack-resistant and robustness of the proposed approach. The experiment results also demonstrate the feasibility and benefit of the approach.

Suggested Citation

  • Jun Li & Xiaolin Zheng & Deren Chen & William Wei Song, 2012. "Trust Based Service Selection in Service Oriented Environment," International Journal of Web Services Research (IJWSR), IGI Global, vol. 9(3), pages 23-42, July.
  • Handle: RePEc:igg:jwsr00:v:9:y:2012:i:3:p:23-42
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    Cited by:

    1. Liu, Yun & Heidari, Ali Asghar & Ye, Xiaojia & Liang, Guoxi & Chen, Huiling & He, Caitou, 2021. "Boosting slime mould algorithm for parameter identification of photovoltaic models," Energy, Elsevier, vol. 234(C).

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