Snowball Framework for Web Service Composition in SOA Applications

Abstract: Service Oriented Architecture (SOA) has emerged as a promising architectural style that provides software applications with high level of flexibility and reusability. However, in several cases where legacy software components are wrapped to be used as web services the final solution does not completely satisfy the SOA aims of flexibility and reusability. The literature review and the industrial applications show that SOA lacks a formal definition and measurement for optimal granularity of web services. Indeed, wrapping several business functionalities as a coarse-grained web services lacks reusability and flexibility. On the other hand, a huge number of fine-grained web services results in a high coupling between services and large size messages transferred over the Internet. The main research question still concerns with “How to determine an optimal level of service granularity when wrapping business functionalities as web services?” This research proposes the Snowball framework as a promising approach to integrate and compose web services. The framework is made up three-step process. The process uses the rules in deciding the web services that have an optimal granularity that maintains the required performance. To demonstrate and evaluate the framework, we realized a car insurance application that was already implemented by a traditional approach. The results show the efficiency of snowball framework over other approaches.

Mohamed Elkholy, Youcef Baghdadi and Marwa Marzouk. “Snowball Framework for Web Service Composition in SOA Applications”. International Journal of Advanced Computer Science and Applications (IJACSA) 13.1 (2022). http://dx.doi.org/10.14569/IJACSA.2022.0130143

@article{Elkholy2022,
title = {Snowball Framework for Web Service Composition in SOA Applications},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130143},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130143},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Mohamed Elkholy and Youcef Baghdadi and Marwa Marzouk}
}