Service Oriented Computing and Applications

, Volume 1, Issue 2, pp 117–128

Context optimization of AI planning for semantic Web services composition

Authors

    • Institute of Computing TechnologyChinese Academy of Sciences
    • Graduate School of the Chinese Academy of Sciences
  • Liang Chang
    • Institute of Computing TechnologyChinese Academy of Sciences
    • Graduate School of the Chinese Academy of Sciences
  • Fen Lin
    • Institute of Computing TechnologyChinese Academy of Sciences
    • Graduate School of the Chinese Academy of Sciences
  • Zhongzhi Shi
    • Institute of Computing TechnologyChinese Academy of Sciences
Original Research Paper

DOI: 10.1007/s11761-007-0010-3

Cite this article as:
Qiu, L., Chang, L., Lin, F. et al. SOCA (2007) 1: 117. doi:10.1007/s11761-007-0010-3

Abstract

Web services composition techniques are gaining momentum as the opportunity to establish reusable and versatile inter-operability applications. Many researchers propose their composition approach based on planning techniques. We propose our context aware planning method which comprises global planning and local optimization based on context information. The major technical contributions of this paper are: (1) We propose an ontology-based framework for the context-aware composition of Web services. Context model, which are structured based on OWL-S, captures the Service-related, Environment-related, and User-related context and can be used in an unambiguous, machine interpretable form. (2) We propose context-aware plan architecture and thus is more scalability and flexibility for the planning process, and thereby improving the efficiency and precision. (3) We propose a hybrid approach to build a plan corresponding to a context-aware service composition, based on global planning and local optimization, considering both the usability and adoption. We test our approach on a simple, yet realistic example, and the preliminary results demonstrate that our implementation provides a practical solution.

Keywords

SOAAI planningStatechartContext-aware

Copyright information

© Springer-Verlag London Limited 2007