Reliable and efficient service composition based on smart objects' state information

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.