Autonomic Execution of Web Service Composition Using AI Planning Method

Autonomic Execution of Web Service Composition Using AI Planning Method

Chao-Qun Yuan, Fang-Fang Chua
Copyright: © 2015 |Pages: 18
DOI: 10.4018/IJITSA.2015010102
OnDemand:
(Individual Articles)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

Web Service Composition is one of the technologies in Service Oriented Architecture which significantly increases the flexibility and reusability of developing service-oriented system. One of the major problems which occurs in web service composition is the difficulties of maintaining the existing running web service composition solutions due to the changes of business requirements, deployment environment, and other dynamic factors. In this proposed work, an automated system had been built to autonomously execute the web service composition. To achieve this objective, the authors had embedded semantic engine and Prolog in C# program to automatically and dynamically discover, compose and execute web service composition, i.e. a web service composition could be self-configured to automatically recover from execution failure and automatically re-generate composition solution due to business protocol changes.
Article Preview
Top

Several research efforts have been done on automatic service composition. (Sirin, 2010) and (Srivastava & Koehler, 2003) have proposed such method by using semantic annotated web services and AI planning to implement automatic and dynamic web service composition. (Rao & Su, 2005) and (Peer, 2005) also conducted a survey on web service composition using AI planning. In the following sections we will introduce some of the AI planning methods and their implementation in automatic web service composition.

Complete Article List

Search this Journal:
Reset
Volume 17: 1 Issue (2024)
Volume 16: 3 Issues (2023)
Volume 15: 3 Issues (2022)
Volume 14: 2 Issues (2021)
Volume 13: 2 Issues (2020)
Volume 12: 2 Issues (2019)
Volume 11: 2 Issues (2018)
Volume 10: 2 Issues (2017)
Volume 9: 2 Issues (2016)
Volume 8: 2 Issues (2015)
Volume 7: 2 Issues (2014)
Volume 6: 2 Issues (2013)
Volume 5: 2 Issues (2012)
Volume 4: 2 Issues (2011)
Volume 3: 2 Issues (2010)
Volume 2: 2 Issues (2009)
Volume 1: 2 Issues (2008)
View Complete Journal Contents Listing