A Probabilistic QoS Model and Computation Framework for Web Services-Based Workflows

San Yih Hwang, Haojun Wang, Jaideep Srivastava, Raymond A. Paul

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


Web services promise to become a key enabling technology for B2B e-commerce. Several languages have been proposed to compose Web services into workflows. The QoS of the Web services-based workflows may play an essential role in choosing constituent Web services and determining service level agreement with their users. In this paper, we identify a set of QoS metrics in the context of Web services and propose a unified probabilistic model for describing QoS values of (atomic/composite) Web services. In our model, each QoS measure of a Web service is regarded as a discrete random variable with probability mass function (PMF). We describe a computation framework to derive QoS values of a Web services-based workflow. Two algorithms are proposed to reduce the sample space size when combining PMFs. The experimental results show that our computation framework is efficient and results in PMFs that are very close to the real model.

Original languageEnglish (US)
Pages (from-to)596-609
Number of pages14
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
StatePublished - Dec 1 2004


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