Please use this identifier to cite or link to this item:
Title: Reliable and efficient service composition based on smart objects' state information
Authors: Feng, Y
Cao, J 
Sun, Y
Wu, W
Chen, C
Ma, J
Issue Date: 2010
Source: Journal of ambient intelligence and humanized computing, 2010, v. 1, no. 3, p. 147-161 How to cite?
Journal: Journal of Ambient Intelligence and Humanized Computing 
Abstract: Service composition is a mechanism to combine two or more services to form a composite service for delivering the users' desirable functionalities. Existing service composition system in pervasive computing does not capture state information of the smart objects (SOs). Based on the study of relationships of SOs' states and services, we identify unqualified composite services generated by existing service composition systems, which are either inefficiently executed or fail to complete their execution. This handicaps the applications of pervasive computing because its applications like health care normally need more reliable and timing services. In this paper, we first formally model SOs' states and their transitions using finite state machines and propose extending existing service description technologies using the SOs'state information. The obtained information is then used in designing an algorithm to compose SOs' services, which avoids generating the identified unqualified composite services. The proof of the efficiency of the composite services obtained by our proposed algorithms is elaborated. Finally, a performance study was conducted to evaluate our algorithm against the one without considering SO state information. Our experimental results show that the composite services generated using our algorithm can execute faster and more reliably.
ISSN: 1868-5137
DOI: 10.1007/s12652-010-0017-z
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Aug 14, 2017

Page view(s)

Last Week
Last month
Checked on Aug 13, 2017

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.