A probabilistic approach to modeling and estimating the QoS of web-services-based workflows

  • Authors:

  • San-Yih Hwang;Haojun Wang;Jian Tang;Jaideep Srivastava

  • Affiliations:

  • Department of Information Management, National Sun Yat-sen University, Kaohsiung 80424, Taiwan;Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA;Department of Computer Science, Memorial University of Newfoundland, St. John's, Newfoundland, Canada A1B 3X5;Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2007

Quantified Score

Hi-index 0.07

Visualization

Abstract

Web services promise to become a key enabling technology for B2B e-commerce. One of the most-touted features of Web services is their capability to recursively construct a Web service as a workflow of other existing Web services. The quality of service (QoS) of Web-services-based workflows may be an essential determinant when selecting constituent Web services and determining the service-level agreement with users. To make such a selection possible, it is essential to estimate the QoS of a WS workflow based on the QoSs of its constituent WSs. In the context of WS workflow, this estimation can be made by a method called QoS aggregation. While most of the existing work on QoS aggregation treats the QoS as a deterministic value, we argue that due to some uncertainty related to a WS, it is more realistic to model its QoS as a random variable, and estimate the QoS of a WS workflow probabilistically. In this paper, we identify a set of QoS metrics in the context of WS workflows, and propose a unified probabilistic model for describing QoS values of a broader spectrum of atomic and composite Web services. Emulation data are used to demonstrate the efficiency and accuracy of the proposed approach.