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 journalArticle

24 Citations (Scopus)

Abstract

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
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)
Volume3288
Publication statusPublished - 2004
Externally publishedYes

Fingerprint

Workflow
Statistical Models
Web services
Work Flow
Web Services
Quality of service
Sample Size
Language
Model
Technology
Discrete random variable
Sample space
Service Level Agreement
Framework
Electronic Commerce
Random variables
Probabilistic Model
Composite
Metric
Composite materials

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

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