Cart (Loading....) | Create Account
Close category search window

A Temporal Data-Mining Approach for Discovering End-to-End Transaction Flows

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

8 Author(s)
Ting Wang ; Georgia Inst. of Technol., Atlanta, GA ; Chang-shing Perng ; Tao Tao ; Chungqiang Tang
more authors

Effective management of Web Services systems relies on accurate understanding of end-to-end transaction flows, which may change over time as the service composition evolves. This work takes a data mining approach to automatically recovering end-to-end transaction flows from (potentially obscure) monitoring events produced by monitoring tools. We classify the caller-callee relationships among monitoring events into three categories(identity, direct-invoke, and cascaded-invoke), and propose unsupervised learning algorithms to generate rules for each type of relationship. The key idea is to leverage the temporal information available in the monitoring data and extract patterns that have statistical significance. By piecing together the caller-callee relationships a teach step along the invocation path, we can recover the end-to-end flow for every executed transaction. Experiments demonstrate that our algorithms outperform human experts in terms of solution quality, scale well with the data size, and are robust against noises in monitoring data.

Published in:

Web Services, 2008. ICWS '08. IEEE International Conference on

Date of Conference:

23-26 Sept. 2008

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.