| Title | Web Service Selection with Correlations: A Feature-Based Abstraction Refinement Approach |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Ray, K., Banerjee, A., Mohalik, S. K. |
| Conference Name | 2019 IEEE 12th Conference on Service-Oriented Computing and Applications (SOCA) |
| Date Published | nov |
| Keywords | candidate services, composability, Correlation, feature selection, feature-based abstraction refinement technique, Human Behavior, Internet-scale Computing Security, linear workflow, Metrics, optimisation, Optimization, ordered tasks, policy governance, Proposals, pubcrawl, Resiliency, Scalability, service selection, set theory, Silicon compounds, Task Analysis, Web service benchmarks, Web service selection problem, web services, workflow |
| Abstract | In this paper, we address the web service selection problem for linear workflows. Given a linear workflow specifying a set of ordered tasks and a set of candidate services providing different features for each task, the selection problem deals with the objective of selecting the most eligible service for each task, given the ordering specified. A number of approaches to solving the selection problem have been proposed in literature. With web services growing at an incredible pace, service selection at the Internet scale has resurfaced as a problem of recent research interest. In this work, we present our approach to the selection problem using an abstraction refinement technique to address the scalability limitations of contemporary approaches. Experiments on web service benchmarks show that our approach can add substantial performance benefits in terms of space when compared to an approach without our optimization. |
| DOI | 10.1109/SOCA.2019.00013 |
| Citation Key | ray_web_2019 |
Web Service Selection with Correlations: A Feature-Based Abstraction Refinement Approach