WSBen: A Web Services Discovery and Composition Benchmark Toolkit

WSBen: A Web Services Discovery and Composition Benchmark Toolkit

Seog-Chan Oh (General Motors R&D Center, USA) and Dongwon Lee (The Pennsylvania State University, USA)
Copyright: © 2010 |Pages: 20
DOI: 10.4018/978-1-60566-982-3.ch040

Abstract

In this article, a novel benchmark toolkit, WSBen, for testing web services discovery and composition algorithms is presented. The WSBen includes: (1) a collection of synthetically generated web services files in WSDL format with diverse data and model characteristics; (2) queries for testing discovery and composition algorithms; (3) auxiliary files to do statistical analysis on the WSDL test sets; (4) converted WSDL test sets that conventional AI planners can read; and (5) a graphical interface to control all these behaviors. Users can finetune the generated WSDL test files by varying underlying network models. To illustrate the application of the WSBen, in addition, we present case studies from three domains: (1) web service composition; (2) AI planning; and (3) the laws of networks in Physics community. It is our hope that WSBen will provide useful insights in evaluating the performance of web services discovery and composition algorithms. The WSBen toolkit is available at: http://pike.psu.edu/sw/wsben/.

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