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Supporting the dynamic evolution of Web service protocols in service-oriented architectures
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ACM Transactions on the Web (TWEB) archive
Volume 2 ,  Issue 2  (April 2008) table of contents
Article No. 13  
Year of Publication: 2008
ISSN:1559-1131
Authors
Seung Hwan Ryu  University of New South Wales, Sydney, NSW, Australia
Fabio Casati  University of Trento, Povo (Trento), Italy
Halvard Skogsrud  ThoughtWorks, Sydney, NSW, Australia
Boualem Benatallah  University of New South Wales, Sydney, NSW, Australia
Régis Saint-Paul  University of New South Wales, Sydney, NSW, Australia
Publisher
ACM  New York, NY, USA
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DOI Bookmark: 10.1145/1346237.1346241

ABSTRACT

In service-oriented architectures, everything is a service and everyone is a service provider. Web services (or simply services) are loosely coupled software components that are published, discovered, and invoked across the Web. As the use of Web service grows, in order to correctly interact with them, it is important to understand the business protocols that provide clients with the information on how to interact with services. In dynamic Web service environments, service providers need to constantly adapt their business protocols for reflecting the restrictions and requirements proposed by new applications, new business strategies, and new laws, or for fixing problems found in the protocol definition. However, the effective management of such a protocol evolution raises critical problems: one of the most critical issues is how to handle instances running under the old protocol when it has been changed. Simple solutions, such as aborting them or allowing them to continue to run according to the old protocol, can be considered, but they are inapplicable for many reasons (for example, the loss of work already done and the critical nature of work). In this article, we present a framework that supports service managers in managing the business protocol evolution by providing several features, such as a variety of protocol change impact analyses automatically determining which ongoing instances can be migrated to the new version of protocol, and data mining techniques inferring interaction patterns used for classifying ongoing instances migrateable to the new protocol. To support the protocol evolution process, we have also developed database-backed GUI tools on top of our existing system. The proposed approach and tools can help service managers in managing the evolution of ongoing instances when the business protocols of services with which they are interacting have changed.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Seung Hwan Ryu: colleagues
Fabio Casati: colleagues
Halvard Skogsrud: colleagues
Boualem Benatallah: colleagues
Régis Saint-Paul: colleagues