Abstract
Service composition which integrates the functionalities of different services is a promising technique for developing applications especially for across multiple organizations. The dependability of Web services, however, is limited in some important ways for the distributed, dynamic and autonomous service domains. This paper addresses this problem by proposing dependable and adaptive approach for Service Composition. This paper initially transforms the composite services dependability maintain problem to a adaptive control problem, modeling the control process as a Markov decision process and therefore, it proposes an adaptive control system architecture, then designs and optimizes the maintenance strategy in accordance with control goals given in the setting of the theory of Markov Decision Process. It further gives Reinforcement Learning Based Adaptive Control Mechanism and corresponding algorithm to maintain the dependability of composite service. Finally this paper implements a prototype system to evaluate the proposed approach through comprehensive experiments and achieves improved results.
| Original language | English |
|---|---|
| Pages (from-to) | 1434-1444 |
| Number of pages | 11 |
| Journal | Jisuanji Xuebao/Chinese Journal of Computers |
| Volume | 31 |
| Issue number | 8 |
| DOIs | |
| State | Published - Aug 2008 |
Keywords
- Adaptive control
- Dependability
- Q learning algorithm
- Reinforcement learning
- Service composition
Fingerprint
Dive into the research topics of 'Dependable and adaptive approach to supporting Web service composition'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver