Abstract
This article proposes an approach for predicting runtime of web services (WS) with state – also called stateful web services. Estimating WS runtime is particularly critical during construction of composite WS workflows. Each workflow job must be scheduled in a way that the overall workflow run time will satisfy the overall workflow constrains. Such workflows are commonly used in Grids for connecting individual Grid WS to large, complicated and distributed applications. Prediction of WS run times optimizes scheduling and supports efficient use of grid resources. In our approach we propose to estimate expected WS run time based on invocation parameters of WS operations, states of resources maintained by a WS and properties of resources used as processing inputs for a WS. We adopt knowledge based approach where the history of WS operations is examined and a model is created and updated for each class and instance of a WS. Such WS run time prediction models can be then used by workflow schedulers to compute expected run times of a range of WS for the purpose of identifying the most appropriate WS for a given job within given constrains.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Web Services Notification: http://www-106.ibm.com/developerworks/library/specification/ws-notification/
Web Service Management: Service Life Cycle: http://www.w3.org/TR/2004/NOTE-wslc-20040211/
EU IST: K-Wf Grid Project IST-2002-511385, http://www.kwfgrid.net/
EU IST: CrossGrid Project IST-2001-32243, http://www.crossgrid.org/
Delpoi Grid(Lab)? Adaptive Component System: http://www.gridlab.org/WorkPackages/wp-7/
Faerman, M., Su, A., Wolski, R., Berman, F.: Adaptive Performance Prediction for Distributed Data-Intensive Applications. In: Proceedings of the ACM/IEEE SC 1999 Conference on High Performance Networking and Computing, Portland, August 9 (1999)
Balogh, Z., Laclavik, M., Hluchy, L., Nguyen, T.G., Gatial, E.: Capture, Discovery and Reuse of Knowledge in REMARK. In: ICETA 2004, Kosice, Slovakia, September 2004, IEEE Computer Society, Los Alamitos (2004)
Menasce, D.A., Virgilio, A.F.: Capacity Planning for Web Services - Metrics, Models, and Methods. Prentice-Hall, Englewood Cliffs (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Balogh, Z., Gatial, E., Laclavik, M., Maliska, M., Hluchy, L. (2006). Knowledge-Based Runtime Prediction of Stateful Web Services for Optimal Workflow Construction. In: Wyrzykowski, R., Dongarra, J., Meyer, N., Waśniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2005. Lecture Notes in Computer Science, vol 3911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752578_72
Download citation
DOI: https://doi.org/10.1007/11752578_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34141-3
Online ISBN: 978-3-540-34142-0
eBook Packages: Computer ScienceComputer Science (R0)