GOS: a global optimal selection strategies for QoS-aware web services composition

  • Authors:

  • Mu Li;Danfeng Zhu;Ting Deng;Hailong Sun;Huipeng Guo;Xudong Liu

  • Affiliations:

  • School of Computer Science and Engineering, Beihang University, Beijing, China;School of Computer Science and Engineering, Beihang University, Beijing, China;School of Computer Science and Engineering, Beihang University, Beijing, China;School of Computer Science and Engineering, Beihang University, Beijing, China;School of Economics and Management, Beihang University, Beijing, China;School of Computer Science and Engineering, Beihang University, Beijing, China

  • Venue:
  • Service Oriented Computing and Applications
  • Year:
  • 2013

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Abstract

Services composition technology provides a promising way to create new services in services-oriented architecture. However, some challenges are hindering the application of services composition. One of the major challenges encountered by composite services developer is how to effectively select a set of services across different autonomous regions (e.g., organization or business) to instantiate a composite service which can satisfy user's QoS constraints. To solve QoS-aware Web service composition problem, this paper proposes a global optimization selection (GOS) approach based on prediction mechanism for QoS values of local services. The GOS includes two parts. First, the local preprocessing service selection algorithm can be used to increase composite services performance in run-time by predicting the change of service quality parameters. Second, GOS aims at enhancing the run-time performance of global selection by reducing QoS aggregation operations. The simulation results show that the GOS has excellent selection and lower execution cost than existing approaches.